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PSC training provides an introduction to conceptual and technical approaches in research and also up-to-date methodological knowledge from research frontiers in plant sciences. Our workshops aim to enhance your interdisciplinary research competence in the field of plant sciences. PSC also offers training on developing transferable skills.
Be aware that not all courses are offered annually.
PSC aims to mediate additional tools at the interfaces between research, policy, and diverse stakeholders and offers specialised courses in Science & Policy.
The colloquium “Challenges in Plant Sciences” is a core event of the Plant Science Center's PhD program and the MSc module. The colloquium introduces participants to the broad spectrum of disciplines in plant sciences. The topics offer integrated knowledge about plant sciences, from the molecular level to the ecosystem level, and from basic to applied science while making use of the synergies between the different research groups of the PSC.
The course offers a unique chance to approach interdisciplinary topics as challenges in the field of plant sciences. During the kick-off meeting, lecturers give talks on various topics as a general introduction to their research fields. Subsequently, each student group prepares a presentation chosen from a variety of topics and based on literature provided by the lecturers. Students broaden their knowledge in plant sciences. They also practice their lecturing skills and discuss research publications.
Individual Performance and Assessment: 2 Credit Points for PhD and Master students. Based on 8 days of work (= 60 learning hours) consisting of 2 days block course and 6 days of independent preparation time for the talk.
2 ECTS (60 learning hours)
Annually (fall semester)
PSC professors and group leaders
► This course addresses PhD and Master's students
All students who started their PhD after February 2016 have to participate in the Scientific Integrity – Introduction Event (2 hours, no ECTS, Introduction to GSP & Scientific Integrity) offered by the Life Science Zurich Graduate School LSZGS.
Please, register via LSZGS
At the end students sign the declaration of “Good scientific practice” that becomes part of their DissGo documents. PhD students planning to participate in a more extensive course on “Research Integrity” or “Ethics” during their PhD program don’t need to visit this introduction event. For all accredited Scientific Integrity training courses check the Scientific integrity training course catalogue.
Resolving the subcellular localization of a fluorescent compound in intact plant tissues or whole organs is a challenging task. Specific problems are posed by the high refractive nature of fresh tissues, sample thickness and stress-induced autofluorescence in dissected tissues. Together with classical problems of photobleaching and phototoxicity, these plants-specific issues make high-resolution and time-lapse imaging of fluorescent reporter proteins (or counterstaining) dye very challenging.
The aim of this course is to obtain both an overview and a specific practice. First, this course will give an overview of available microscopy imaging solutions depending on applications. We will specifically practice confocal laser scanning microscopy imaging of Arabidopsis tissues using different mounting and clearing agents; the aim is to learn customizing the acquisition parameters towards maximum possible resolution within specific constraints of speed, viability, bleaching and signal diffraction levels in fresh vs. fixed tissues. The course also offers a brief introduction to high-resolution two-photon microscopy for deep tissue imaging.
Secondly, we will learn to exploite the benefits of 3D imaging at the qualitative and quantitative level. We will practice 3D volume rendering, preparation of attractive image material for publication, image segmentation and extraction of quantitative information for statistical analyses.
Individual Performance and Assessment: In order to complete the course and to receive the credit point, students will be required to attend the whole course and to actively participate.
Prior knowledge: The course is designed for students with a prior experience in CSLM imaging and whose research involves (or will involve) 3D imaging in plant tissues. Applicants are welcome to bring their own samples and should contact the coordinator beforehand.
1 ECTS (30 learning hours)
Every two years (next 2022)
Lecturer: Célia Baroux (UZH, Coordinator) and Alexis Maizel (Guest speaker), Center for Organism Science, University of Heidelberg
It’s a comprehensive graduate course on alpine plant life in the Swiss central Alps, jointly organized by the University of Basel and the Zurich-Basel Plant Science Center (PSC) for graduate students with basic training in plant science. The course covers microclimatology, vegetation ecology, reproduction biology, aspects of biodiversity, soil science, ecophysiology and ecosystem ecology. Morning and evening lectures, field excursions and team-work on small projects will make this week, in a truly alpine environment, a life time experience. The ALPFOR research station is surrounded by a great variety of typical alpine vegetation, including glacier forfields.
Individual performance and assessment: Credits will be given on a pass/fail basis (active participation, design and presentation of a mini-poster).
3 ECTS (90 learning hours)
Annually (Spring semester)
Lecturer: Dr. Erika Hiltbrunner, Prof. Christian Körner, University of Basel, et al.
Identification based on host, symptoms and micro-morphology, completed with life cycles and related control measures of the most important fungal diseases and their causal pathogens of selected annual and perennial crops. A half-day excursion will be integrated to allow applied training of symptom recognition in the field. The students will learn and train preparation skills for microscopy, acquire basic knowledge of selected diseases (Identification, Biology of pathogen, Epidemiology) and understand the corresponding integrated control measures practiced in Swiss agriculture.
Individual Performance and Assessment: Active participation in the exercises is required. In a final test individual skills of microscopical preparation and recognition of structures important for diagnosis are assessed.
1 ECTS (30 learning hours)
Every two years (last FS 2021, next 2023)
Lecturer: Prof. Dr. Monika Maurhofer, ETH Zurich and Jana Schneider
Chlorophyll fluorescence analysis is one of the most powerful and widely used techniques by plant physiologists and ecophysiologists. Chlorophyll fluorescence is used for rapid non-invasive measurement of photosystem II activity. PSII activity is very sensitive to range of biotic and abiotic factors and therefore chlorophyll fluorescence technique is used as rapid indicator of photosynthetic performance of plants in different developmental stages and/or in response to changing environment. The course will consist of lectures related to the theoretical background of this technique and practicals where different measuring protocols will be used to illustrate the types of information that fluorescence can provide. We will use both imaging and non-imaging tools for analysis of chlorophyll fluorescence kinetics. The analysed samples will be plants from Arabidopsis thaliana, including mutants affected in photosynthetic acclimation mechanisms as a case study.
Individual Performance and Assessment: At the end of the course the students will be asked to prepare a short report and present how they can use Chl fluorescence in their research. They will briefly present the background, problem, design and the experiments that could be performed.
1 ECTS (30 learning hours)
Biannually (last 2022, next 2024)
Lecturer: Dr Diana Santelia, ETHZ; Klára Panzarová, Photon Systems Instruments (PSI); Tracy Lawson, University of Essex (UK), Fiamma Longoni, University of Neuchâtel.
In collaboration with URPP
Concepts in evolutionary biology are often used ambiguously, partly because the same terms may have different usage in other fields in biology. The course is designed for graduate students with interdisciplinary projects encompassing evolutionary biology and other disciplines. It provides lectures and simple calculation exercises in population and quantitative genetics.
1 ECTS (30 learning hours)
Annually (autumn semester)
Lecturer: Prof. Barbara König, Prof. Lukas Keller, Prof. Michael Krützen, Prof. Marcelo Sanchez, Prof. Kentaro Shimizu, Prof. Anne Roulin, Dr. Anna K. Lindholm Krützen, University of Zurich
Given current discussions and efforts towards more sustainable agricultural production systems, we will investigate what plant breeding can contribute i) to reduce the input of plant protection products, ii) to make our crops genetically ready for future climatic conditions and iii) to evaluate what traits might become important in alternative production systems.
The educational objectives cover both thematic competences and soft skills:
Thematic competences:
Soft skills:
Individual Performance and Assessment: On November 6, 2020, from 2 to 5pm, the enrolled students will be introduced to the concept, topic and the lecturers/tutors involved in 'Current challenges in plant breeding'. After an input talk by the lecturers, four to six specific aspects/questions for the above-mentioned topics will be identified and phrased. The tutors and the enrolled students will be assigned to four to six different groups, to critically evaluate one aspect/question. The students, guided by tutors, will prepare a presentation of 15 minutes (plus 5 minutes discussion) covering their specific question/aspect. Participation in this introductory lecture mandatory.
On January 26, 2021, a one-day seminar on the selected topic will be organized. The presentations of the students will be complemented with keynote talks from national and international experts. The seminar will be public and serve as annual meeting of the 'Working Group Plant Breeding' from the Swiss Society of Agronomy, bringing together the experts in plant breeding.
2 ECTS (60h learning hours)
Annually (Fall semester)
Lecturer: Prof. Bruno Studer and Dr. Andreas Hund, ETH Zurich
This course provides training for advanced students (master, doctoral or post-doctoral level) in how to measure and collect genetic diversity data from populations, experiments, field and laboratory. Different DNA/RNA extraction, genotyping and gene expression techniques will be addressed. After an introduction (one afternoon), students will have 3 weeks to work in groups of two through different protocols according to their timetable. At the end, the whole group meets for another afternoon to present the techniques/results and to discuss the advantages and disadvantages of the different techniques. Examples are: RNA/DNA extraction, SNP genotyping, pyrosequencing, real-time qPCR.
Individual Performance and Assessment: Students have to attend on the two afternoons (8 hours) and do the individual work in between (around 52 hours). At the end they have to present a technique and their results in a talk.
1 ECTS (30 learning hours)
Annually (Fall semester)
Lecturer: Dr. Aria M. Minder, ETH Zurich
The course will provide hands-on training for advanced students (e.g. master, doctoral or post-doctoral level) in genomic data analysis. The focus is on high-throughput sequencing applications and data analysis with a strong emphasis on reproducibility and report writing. We cover the fundamentals of bio-computing. Exercises will help to better understand the theory. It is, however, not a copy-paste course, but a more applied data analysis with discussion.
The course extends over two weeks so that the participants have enough time to digest and apply what they have learned at their own pace. It is our goal that the course participants understand the applications and have time to question them. Have a look at our previous course website and current course website for more details.
Individual Performance and Assessment: You have the chance to work on a project of your choice with you own data. Students interested in the credit points have to hand in a project report.
2 ECTS (60 learning hours)
Annually (Spring semester)
Lecturer: Dr. Jean-Claude Walser & Dr. Niklaus Zemp, Genetic Diversity Center, ETH Zurich
Crops are exposed to different abiotic stress factors during their development. Adaptation of crops to extreme environmental conditions during the course of the growing season (e.g. cold and heat stress; water-saturated or dry soils) has been achieved by plant breeding in the last century. However, there is enormous potential for optimization by means of modern crop phenotyping.
In this course, the most important mechanisms of plant adjustment towards stress will be explained, as well as critical stages identified in which stress affects yield most severely. We will dissect growth and development into three main trait categories which can be related to ideotype concepts:
(i) Timing of key stages;
(ii) Quantities at defined time points or periods and
(iii) Dose-response curves.
The lecture will put a strong focus on hands-on experience for both the handling of plants and sensors as well as coding in R and Python. You will learn how to use passive imaging sensors, like thermal, hyperspectral or RGB cameras but also active sensors like laser scanners and chlorophyll fluorometers. You will set up your own R and Python environment and work on different aspects of the whole crop phenotyping workflow in small expert-teams. Each team will contribute a piece of information to the common phenotyping experiment which will be presented jointly at the final field day in June. At this day, different experts from ETH, Agroscope and Syngenta will provide hands-on experience in the field. See abstract for more details..
Individual Performance and Assessment: PhD students will take part in the MSc course 751-4106-00 G Crop Phenotyping. A reduced workload will allow to acquire 2 ECTS points: Participants enrolled in the PSC are required to i) give a presentation, ii) participate in the group work carried out during the season, and iii) submit one of 5 exercises.
2 ECTS (60 learning hours)
annually (last spring 2021)
Lecturer: Dr. Andreas Hund, Lukas Roth, Jonas Anderegg, Prof. Achim Walter, Jörg Leipner (ETHZ)
The aim of the course is to enable participants to design and interpret functional genomics experiments and critically evaluate available technical options. Demonstrations of available technologies at the FGCZ will be included. In the postgenomic era emphasis of research shifts from merely accumulating sequence data towards the identification of functional significance of gene products. The goal of functional genomics is to understand the relationship between genome sequence and phenotype. An important aspect here is the measurement of molecular activities with the high-throughput ‘omics’ technologies transcriptomics, proteomics and metabolomics. The course comprises a theoretical introduction to mass spectrometry, the key technology for protein and metabolite analyses, and to transcriptional profiling. The diverse set of available technologies and most recent developments will be presented, including bioinformatic approaches to analyse data and comprehend large amounts of data.
Individual Performance and Assessment: In order to obtain the credit point, active participation during all three courses days is mandatory.
1 ECTS (30 learning hours)
Every two years (last 2017, next to be announced)
Lecturer: Dr. Bernd Roschitzki, Dr. Endre Laczko, Andrea Patrignani, Dr. Lucy Poveda and Dr. Giancarlo Russo (Functional Genomics Center Zurich)
In collaboration with URPP
In this course, we will discuss the pre-eminent tool for identifying genes that underlie natural phenotypic variation: genome-wide association studies (GWAS). Originally developed by human geneticists to fine-map genes that underlie human disease, GWAS have the capacity to revolutionize all of the biological sciences. Plant biologists, in particular, have already taken advantage of improvements in sequencing technology in order to characterize genetic variation across the genomes of several species. Doing so has enabled the use of GWAS to fine-map genes that underlie ecologically and agriculturally relevant traits. At the beginning of the course, we will provide an introduction to GWAS. Then, we will discuss the history of gene mapping and the genetic and statistical background on which GWAS are based. The course has a strong practical component, and students will gain experience analyzing real data on the computer. At the end of the course, students will be able to interpret GWAS results and carry out their own analyses. We will also discuss basic concepts (and challenges) in population genetics, genomics, and quantitative genetics. For preparation, the students will have to read some literature which will be sent out prior to the course.
Individual Performance and Assessment: This 2-day course will be split between lectures and tutorials. Required: attendance, active participation during the exercises (16 hours) and handing in of an individual exercise after the course (14 hours of preparation work).
1 ECTS (30 learning hours)
Biannually (last 2020, next HS 2022)
Lecturer: Prof. Dr. Thomas Wicker (UZH)
Light microscopy is a frequently used tool in plant sciences. Still, many are not aware of all the factors that are necessary for good quality, reproducible microscopy images. The aim of the course is to give the participants a practice-oriented introduction to the basics of light microscopy, including a short introduction to image processing. This 3-day course offers a basic introduction into light microscopy. During the mornings lectures will summarize the necessary theory and the afternoon session will concentrate on practical, hands-on exercises. The following subjects will be dealt with transmission microscopy (phase contrast, DIC), fluorescence microscopy (including confocal imaging), basics of image processing.
Individual Performance and Assessment: Active participation during the course and in the hands-on training is necessary.
1 ECTS (30 learning hours)
Every two years (last autumn 2021, next 2023)
Lecturer: Dr. Gábor Csúc and Nicolas Blanc, ETH Zurich,
In collaboration with URPP
The aim of this course is to introduce students to the Linux/Unix command line and shell scripting by taking a hands-on approach. Short lectures present an overview of the Linux/Unix command line focusing on commands for working with files/directories and text files. Students also practice how to install and run software. Participants learn how to write simple shell scripts as they are often used to automate repetitive tasks and to build software pipelines. They will also discuss recommendations for reproducible research such as good coding practices. The course is composed of lectures and guided computer exercises. Students will spend most of the time solving computer exercises.
Individual Performance and Assessment: Attendance at lectures and active participation in the hands-on exercises are required.
0 ECTS (8 learning hours)
Annually (last spring 2021)
Lecturer: Dr. Deepak Tanwar (UZH)
In collaboration with URPP
Handling of the huge data produced by next generation sequencers (NGS) requires us experimental knowledge and computational skills. The aim of this course is to familiarize the participants with experimental methods and data analysis about NGS. Topics will include: fundamental analysis of the sequence data, UNIX tools, and RNA-seq analysis. Learning outcomes are: - Understand concepts of NGS technologies, - Understand basic operation of UNIX operating system, - Design a research experiment and the data analysis involving biologically relevant issues affecting populations of plants or animals, - Map NGS data onto a reference genome and estimate gene expression level, - Understand differential gene expression and polymorphism analysis using NGS data, - Understand algorithms of De novo assembly and alignment of NGS data, and - Understand basic bioinformatics of large datasets for practical use in genetic analyses.
Individual Performance and Assessment: Attendance at lectures and active participation in the hands-on exercises are required.
1 ECTS (30 learning hours)
Annually (fall semester)
Lecturer: Prof. Kentaro Shimizu, Prof. Jun Sese (Japan), Dr. Rie Inatsugi, Dr. Masaomi Hatakeyama and Dr. Jianqiang Sun, UZH
In collaboration with URPP
The goal is to introduce the students into data processing and analysis used in next-generation sequencing (NGS). Based on the course BIO610 "Next-Generation Sequencing for Model and Non-Model Species" it will extend knowledge of NGS analysis and skills in computing taking a hands-on approach.
Individual Performance and Assessment: Attendance at lectures and active participation in the hands-on exercises are required.
1 ECTS (30 learning hours)
Annually (fall semester)
Lecturer: Dr. Gregor Roth and Prof. Kentaro Shimizu (UZH)
The plant-soil microbiome is an essential component of agroecosystems, regulating crop growth, nutrient use efficiency, stress resilience, and disease resistance. In this course, students will develop a fundamental understanding of (i) how microorganisms shape the functioning of the plant-soil system, (ii) how ecosystem management and global changes are influencing diversity and functioning of these microbial systems, and (iii) how the microbiome might be managed to improve sustainable agricultural production. A strong focus will be placed on getting to know the methodological toolbox to study microbes in the environment including different next-generation DNA sequencing applications such as metabarcoding and metagenomics. Theoretical input lectures will be combined with presentations of current research projects. Flipped classroom assignments will be used to critically discuss research findings of specific publications or to evaluate the strength and limitation of the specific methods.
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate in the lectures and flipped classroom assignments.
2 ECTS (56 learning hours)
Annually (Spring semester)
Lecturer: Hartmann Martin, Institute of Agricultural Sciences, ETH Zurich
This computer block course provides a thorough introduction to the application of next-generation sequencing techniques for analyzing diversity of microbial communities with a main focus on the metabarcoding technique. The topics covered by the course range from bioinformatic processing of sequencing data to the most important approaches in multivariate statistics. Using a combination of theoretical lectures and hands-on computer exercises, the participants will learn the computational steps from processing raw sequencing reads down to the final statistical evaluations.
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the four course days.
1 ECTS (28 learning hours)
Annually (Spring semester)
Lecturer: Hartmann Martin, Institute of Agricultural Sciences, ETH Zurich
This course is an introduction to current methods used in the study of polygenetic variation in plants. In particular, we’ll explore the use of quantitative genetic experiments, quantitative trait locus (QTL) analyses, and linkage disequilibrium (LD) mapping as tools for dissecting the genetic details of continuous variation. The course will concentrate on providing students with the basic statistical and conceptual foundation for understanding continuous variation as well as an introduction to various mapping methods and current challenges in QTL cloning. Finally, we will collect phenotypic data on an Arabidopsis thaliana experimental population and conduct basic mapping analyses in a hands-on lab setting.
Individual Performance and Assessment: In order to obtain the ECTS, each participant is required to actively participate in classroom discussions and computer based analyses.
1 ECTS (24 learning hours)
Biannually (last 2021, next 2023)
Lecturer: Prof Ueli Grossniklaus, University of Zurich, Prof. Tom Juenger, University of Texas at Austin
Next-generation sequencing (NGS) technologies have revolutionized many fields in biology. The Functional Genomics Center Zurich (FGCZ) offers a four-day course with hands-on practicals. The aim is to help scientists interested in NGS technologies, particularly applied to RNA sequencing, to gain a better understanding of the techniques available and their applications. The practical consists of a library preparation starting from polyA enriched RNA, followed by a sequencing run on a bench top sequencer. An introduction to the analyses of the resulting data and some exercises will be offered too. The lectures cover existing and upcoming NGS technologies, their applications and the principles of downstream data analysis. By the end of the course participants should be able to make informed decisions about which technology and workflow to apply to solve specific research questions.
Course Program
Library Prep: PolyA RNA-seq library generation: principles and types
Sequencing: Detailed description of available sequencing technologies platforms, Hands-on laboratory work: preparing and performing sequencing runs
Data analysis: Run QC: Criteria for run performance and quality of data, Preprocessing of the raw data, Mapping the data to a reference, Mapping quality control for RNA-seq data, Transcripts expression quantification and tests for differential expression, Set-based analysis (e.g., pathways, GO-categories) IT and awareness of the data storage and its size
Individual Performance and Assessment: Attendance and active participation during all four days of the course (32 hours) plus completing an individual assignment of around 6 hours.
1 ECTS (38 learning hours)
Biannually (last 2018, next to be announced)
Lecturer: Dr. Lucy Poveda, Dr. Weihong Qi and others, Functional Genomics Center Zurich
Scientists are under pressure to communicate with the public about their research. This pressure comes from funding bodies such as the EU, the SNF, the taxpayers, recruiting agencies and policy makers. Improved public and media communication is essential if the public is to better understand who scientists are and what they do. Also, communicating is a source of personal satisfaction. For scientists, it's worth learning the basics of communication early in their careers. This course provides a guide to effective science communication, in theory and practice.
Individual Performance and Assessment: Attendance and active participation during the two course days (16 hours). In the weeks between the two workshop days you should plan for available time for group work and individual work of min. 30-40 hours.
2 ECTS (60 learning hours)
Biannually (last 2021)
Lecturer: Dr. Jacopo Pasotti
The three day interactive workshop is designed to train participants in topics and skills relating to the responsible planning, conduct, analysis and communication of research. During the first two days, participants will explore the principles and challenges of research integrity and reproducibility and will gain a better understanding of best practises. On the first day, Dr. Celine Carret will draw on her experience as professional editor to illustrate the challenges faced by scientists relating to research integrity and mis-conduct. Specific focus will be given to image manipulation issues and challenges around authorship, plagiarism and conflicts of interest. On the second day, participants will discuss good practices in the collection, analysis and reporting of data to ensure transparency and reproducibility, both in the lab and when sharing results with others in the field. On the third day, Dr. Simon F. Nørrelykke will cover the practical aspects of performing and recording reproducible image and data analysis. This will include hands-on training in creation of figures for publication and documentation of scientific image analysis workflows; demonstrated with the open-source software Fiji. We will also discuss how Deep Learning and other Machine Learning approaches are changing image analysis, in turn making proper documentation more important than ever.
Topics covered will include:
Understand good practices and concepts for experimental planning, data acquisition, storage and sharing
Understand how journals deal with integrity issues and author conflicts
Understand the rights and responsibilities of scientists in the conduct and publication of research
Learn how to handle the practical aspects of reproducible image analysis and figure creation
How to record and share image and data analysis workflows and data, in open-source software
How Deep Learning and other machine learning approaches is changing image analysis and making proper documentation of work-flows even more important
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the 3 course days. Moreover, is requires to complete preparatory course work/reading and course exercises (i.e. short presentations, individual assignment) successfully.
1 ECTS (30 learning hours)
Biannually (last: 2019)
Lecturer: Dr. Celine Carret, European Molecular Biology Organization (EMBO), Dr. Simon F. Nørrelykke, Scientific Centre for Optical and Electron Microscopy (ScopeM), ETH Zurich
Future demand in agricultural output is supposed to match the needs of 9-billion people with less input of resources. We will discuss current plant science research in the context of sustainability on the production side. A special focus will be on research on agro-ecological systems and farming system research. Can we transform our agricultural practices and move behind existing paradigms to develop innovative and sustainable agriculture production systems? Where does current research indicate on directions for transformation of current practice and how can we assess and analyze them though research? The seminar is set up as a blended-learning seminar, i.e. a combination of face-to-face meetings and self-organized learning with provided online learning material. The seminar comprises two workshop afternoons and an intensive, well-structured self-study/ group work phase in between the workshops. Students can earn 2 ECTS for successful completion of the seminar.
Key objectives for the seminar are
(1) participants will be able to discuss issues of sustainability in the context of current plant science research topics
(2) participants will be able to phrase their own visions for sustainability in plant sciences, their group work topic and their own MSc or PhD project.
Individual Performance and Assessment: ungraded semester performance. Students will actively participate during the two afternoons with presentations on the second afternoon (8 hours). In between the will independently work in the online course with assignments to be handed in and they will in groups prepare a presentation and essay on a sustainability topic (52 hours).
2 ECTS (60 learning hours)
Annually (Fall semester)
Lecturer: Dr. G. Singh Bhullar, FIBL; Dr. Franz Bender, Agroscope; Dr. Frank Liebisch and Dr. Melanie Paschke, ETH Zurich
► This course addresses PhD and Master's students
The participants understand the specific challenges of inter- and transdisciplinary research in general and in the context of sustainable development in particular. They know methods and concepts to address these challenges and apply them to their research projects. The seminar covers the following topics: Theories and concepts of inter- and transdisciplinary research, The specific challenges of inter- and transdisciplinary research, Involving stakeholders, Collaborating disciplines, Exploration of tools and methods, Analysing participants' projects to improve inter- and transdisciplinary elements.
Individual Performance and Assessment: Ungraded semester performance. Active participation during the course days: 24 hours and preparation work for paper presentation in between (36 hours).
2 ECTS (60 learning hours)
Annually (Fall semester)
Lecturer: M. Stauffacher, C. E. Pohl and B. Vienni Baptista, ETH.
for PhD students at ETH: register via MyStudies.
for PhD students at Uni Basel: you have to register as Special student "University of Basel (UBa)" at ETHZ first.
for PhD students at UZH: you have to register as Special student "University of Zurich (UZH)" at ETHZ first.
In this course, we will focus on omics data (mainly genomics and transcriptomics data) and combined data such as GWAS and eQTL. The course is a mixture of theoretical lectures and interactive, practical sessions. The hands-on training will introduce the most commonly applied tools in the field as well as some maybe less commonly but nonetheless very useful ones. Dependent on the participants’ programming abilities we will use GUI-based tools as well as R/Bioconductor and other scripting languages. Learning Outcomes: Understand the process of visual analytics, Know the basics and do’s and don’ts of visualization, Learn how to visualize large-scale genome data, Learn how to visualize transcriptional regulation and abundance, Understand the challenge of GWAS and eQTL data visualization and learn new approaches to address these challenges.
Individual Performance and Assessment: Active participation is expected on all course days (24 hours). Participants will be given practical tasks, their performance will be assessed by their degree of commitment, ability to apply the theoretical concepts to the task in question and creativity. A summary of the completed task and a course diary will have to be handed in after the course (approx. 6 hours effort)
1 ECTS (30 learning hours)
Biannually (next 2023)
Lecturer: PD Dr. Kay Nieselt, Center for Bioinformatics Tübingen, Integrative Transcriptomics, University of Tübingen
The analysis of large data sets (“big data”) is becoming increasingly important in science and elsewhere. In this course, you will learn how to use R to manage and manipulate large data sets, i.e. to sort, merge, subset, aggregate and reshape data, including outlier detection and gap filling algorithms.
For advanced data manipulation, we are going to use novel developments such as plyr/dplyr (“A Grammar of Data Manipulation”), the pipe operator (%>%) for simpler R-coding and data.table for the fast aggregation of large data sets. Furthermore, we will have a closer look at R-data base connections, MySQL queries and the creation of new data bases from R. Depending on the course progress, there will be scope for individuals to work on small projects and / or their own data sets.
Individual Performance and Assessment: In order to obtain the credit points, participants are required to hand in an assignment to be carried out at home. The details will be explained during the course. The assignment is due no later than one week after the course has ended.
1 ECTS (24 learning hours)
Annually (Spring semester)
Lecturer: Dr. Jan Wunder
Compositional data analysis is a methodology used to describe the parts/compounds of a whole, conveying relative information. Typical examples in different fields are: geology (geochemical elements), medicine (body composition: fat, bone, lean), food industry (food composition: fat, sugar, etc), chemistry (chemical composition), ecology (abundance of different species), agriculture (nutrient balance ionomics), environmental sciences (soil contamination), plant science (water, carbon and nitrogen content, composition of soil or microbial communities, species composition) and genetics (genotype frequency). This type of data appears in most applications, and the interest and importance of consistent statistical methods cannot be underestimated. Compositional data analysis is the solution to the problem of how to perform a proper statistical analysis of this type of data i.e., to solve the problem of spurious correlation as it was named by Karl Pearson. This course will introduce compositional data analysis with emphasis on plant sciences.
Individual Performance and Assessment: tba.
1 ECTS (24 learning hours)
Annually (fall semester 2022)
Lecturer: Dr. Matthias Templ (ZHAW)
together with Ecology Program
In this 6-day blocked course, the participants will learn to analyse experimental and observational data with general linear and linear mixed models. The course will be held as workshop, with lecture-type parts introducing important concepts and exercises in which the participants will work on data sets provided or their own data. A key goal will be that the participants learn to recognize the essential structure of data sets and to implemented them adequately in statistical models with fixed and random effects. Specifically, the course will deal with issues of experimental design, analysis of variance, hypothesis testing, variance components, models with multiple error terms as well as balanced and unbalanced data.
This course is not about generalized linear mixed models [GLMM, non-normal data], although it is possible to deal with such data in the projects.
Individual Performance and Assessment: In order to obtain the ECTS point, each participant is required to actively participate in the case-study work, discussions, and presentations during the course days.
1 ECTS (30 learning hours)
Annually (first: spring 2022)
Lecturer: Dr. Pascal Niklaus (UZH)
In the field of genomics it is paramount to handle larger amounts of data efficiently, securely, and reproducibly. For this reason, the main objective of this course is to provide students the most basic and most crucial sets of skills to work with genomic datasets. The students will not just learn to manage data and run analysis but also to document their workflow in an easy but reproducible way. The course will also cover different aspects of basic statistical analysis for genomics.
Individual Performance and Assessment: The course will be a mix between lectures and hands-on exercise. Required: attendance, active participation during the lectures and especially the exercises. There is an assignment for each topic that needs to be handed in by the end of the course.
1 ECTS (30 learning hours)
Biannually (next 2023)
Lecturer: tab
Tba.
Individual Performance and Assessment: tba.
1 ECTS (30 learning hours)
Annually (NEW fall 2022
Lecturer: Prof. Dr. Jan Dirk Wegner (ETHHZ)
In collaboration with PhD program in Ecology
This course aims to promote and facilitate the thoughtful and critical use of meta-analysis for research synthesis in ecology by: 1) Explaining the principles and advantages of meta-analysis for research synthesis, 2) Demonstrating the range of applications of meta-analysis in ecology, 3) Promoting understanding of the assumptions and limitations of meta-analysis, 4) Providing first-hand experience in question formulation, data extraction, database design, use of software for meta-analysis and report preparation. The course program includes: Lectures on the history of meta-analysis, types of quantitative research synthesis, conversion of ecological data to effect sizes, and question formulation; combining effect sizes across studies and testing for moderators in meta-analysis (meta-regression), practical on conducting meta-analysis using OpenMEE software; publication bias, dealing with varying research quality and non-independence of observations; format of meta-analysis report, review of case studies of meta-analysis in ecology, and critique of meta-analysis. Practical exercises on data extraction and inclusion criteria and metrics of effect size for their own meta-analysis, testing for moderators; testing for publication bias in own dataset, and considering sources of non-independence.
1 ECTS (30 learning hours)
Lecturer: Prof. Dr. Julia Koricheva, UK
This basic introduction to R focuses on the technical aspects of data organisation, handling, analysis and presentation using the wide-spread command line program R. This course is not an introduction to statistics, but lays the foundation to efficiently use statistical applications of R, which are introduced in other courses. No previous experience with programming languages is required. The course addresses students who would like to become familiar with a powerful, single and freely available alternative to spreadsheet programmes (excel), other, less flexible commercial statistical packages (SPSS, Jump, Minitab etc.) and graphics software for presenting data (excel, Sigmaplot etc.). Topics covered include the proper organisation of the workspace, reading and writing data files, using R as a calculator, using logic operators, manipulating data frames, summarising and aggregating data, programming ‘ifelse’ statements, loops, short routines, handling time fields in data frames, drawing and customising graphs. Depending on the course progress, there will be scope for individuals to work on small projects and / or their own data sets.
Individual Performance and Assessment: Attendance and active participation during the course days (16 hours). In order to obtain the credit points, participants are required to hand in an assignment to be carried out at home (preparation work of 14 hours). The details will be explained during the course. The assignment is due no later than one week after the course has ended.
1 ECTS (30 learning hours)
Annually (Fall Semester)
Lecturer: Dr. Jan Wunder
Tba.
Individual Performance and Assessment: tba.
1 ECTS (30 learning hours)
Annually (NEW: Fall 2022)
Lecturer: Frank Pennekamp (UZH)
R Markdown and Shiny are powerful R packages for static and dynamic reports, publications and dashboards that can be created fully reproducible using a highly intuitive notebook interface. In this course, you will learn to create Markdown documents consisting of code, text and the YAML header. We will use CSS files to format our reports and look at further customizations like section headings, citations, cross-references, animations, interactive plots, tables, comments and many more. While the main focus of this course will be on R Markdown, we also will introduce Shiny for interactive web applications, shinythemes and htmlwidgets – and last but not least learn how to embed Shiny into R Markdown docs. Depending on the course progress, there will be scope for individuals to work on small projects and / or their own data sets.
Individual Performance and Assessment: In order to obtain the credit points, participants are required to attend *both* course days and hand in an assignment to be carried out at home. The details will be explained during the course. The assignment is due no later than one week after the course has ended.
1 ECTS (30 learning hours)
Biannually (NEW: Spring Semester 2022)
Lecturer: Dr. Jan Wunder
In statistical modeling, the relationships between a response variable and one or more explanatory variables are estimated. In this class, we consider the theory of linear regression with one or more explanatory variables. Moreover, we also study robust methods and nonlinear models. Several numerical examples will illustrate the theory. You will learn to perform a regression analysis and interpret the results correctly. We will use the statistical software R to get hands-on experience with this. You will also learn to interpret and critique regression analyses done by others.
Individual Performance and Assessment: In order to obtain the credit points, participants are required to attend all course days and hand in an assignment to be carried out at home. The details will be explained during the course. The assignment is due no later than one week after the course has ended.
1 ECTS (30 learning hours)
Biannually (NEW: Spring Semester 2022)
Lecturer: Dr. Matthias Templ (ZHAW) and Barbara Templ (ETHZ)
Visualisations can decide about the success of scientific lectures, poster presentations or journal articles. In this course you will get a very brief introduction into general design principles and guidelines for data visualisations. Based on this theoretical framework we will spend most of the course time to learn how to use R as a powerful graphical software to create a wide range of customised graphics that include - but are not limited to - traditional scatter plots, bar plots, mosaic plots, box plots, density plots, violin plots, and interactive graphics as well as grid-based geographic maps and state-of-the-art multipanel conditioning plots (and many more). You will learn about the two pillars of the R graphics systems, i.e. Traditional and Grid graphics. The course focuses on the latter system and more recent developments such as ggplot2 and other advanced libraries based on the “The grammar of graphics”-concept. Depending on the course progress, there will be scope for students to work on small projects and / or their own data sets.
Individual Performance and Assessment: Attendance and active participation during the course days (16 hours). In order to obtain the credit points, participants are required to hand in an assignment to be carried out at home (preparation work of 14 hours). The details will be explained during the course. The assignment is due no later than one week after the course has ended.
1 ECTS (30 learning hours)
Annually (Fall Semester)
Lecturer: Dr. Jan Wunder
Tba.
Individual Performance and Assessment: otba:
1 ECTS (30 learning hours)
Biannually (last fall 2021, next fall 2023)
Lecturer: Dr. Samer Angelone (University of Basel)
The course includes 2 face-to-face workshop days and one day for homework. PhD students will learn specifically to deal with the whole publication process and to establish a publication workflow: How to manage your open data from the very beginning of a research project, how to plan an open access strategy from choosing journals strategically, to submission, to publication. This includes also guidelines for open data, data sharing agreements and data plans, as well as rich data publications and post-publishing marketing strategies.
Individual Performance and Assessment: In order to obtain the ECTS point, each participant is required to actively participate in the case-study work, discussions, and presentations during the course days. In addition and as part of the homework of day 2, participants are expected to:
1 ECTS (30 learning hours)
Annually (Spring semester)
Lecturer: Dr. Philipp Mayer (science-textflow.ch), André Hoffman, M.A. (Open Access, Hauptbibliothek, UZH), Stefanie Strebel, Data Services & Open Access, University of Zurich, Dr. Melanie Paschke (Zurich-Basel Plant Science Center)
Every project has high scientific and organisational demands. Not only your project work but also other activities, such as organising workshops and meetings, require good planning and management and are the focus of this course. With the help of internationally standardised project management and its tools, the project internal communication as well as the monitoring of results can be simplified. And the experience has shown: project management boosts the performance of researchers and is at the same time a promising basis for the successful collaboration between industry and academia. This course should motivate researchers to develop further their personal leadership qualities and to initiate and coordinate in the near future their own projects.
Individual Performance and Assessment: The students are expected to attend both course days and participate actively during the workshop. Additionally, they are expected to submit the planning of a fictional or real project containing the main models discussed in class.
1 ECTS (30 learning hours)
Biannually (next spring 2022)
Lecturer: Dr. Andrea Degen, eurelations AG
Course Content
This course raises awareness of doctoral students to ethical issues that may arise during their doctorate. After an introduction to ethics and good scientific practice, students use resources that can assist them with ethical decision-making. Students are given the opportunity to apply their knowledge and train their newly acquired skills in an interactive, discipline specific context.
Learning Objectives
Prior Knowledge: none
Number of Participants
10 places for students of UZH and University of Basel that are registered in the PhD Programs of PSC or in LSZGS. All ETH doctoral students: Please register via myStudies. Only for doctoral students.
Individual Performance and Assessment:
You will need to hand in a group case study journal and individual case study journal that will be individually assessed by the lecturers. A group presentation of the respective case study is also part of the overall assessment.
1 ECTS (10 hours of work)
Lecturers: Prof. Nina Buchmann, ETH Zurich, Dr. Melanie Paschke, Zurich-Basel Plant Science Center
► This course addresses PhD and Master's students
The participants of the course are going to
a) learn and practice effective scientific presentations with seven simple elements which will be introduced by the lecturer;
b) communicate in a stress-free, clear and individual way to various audiences (e.g. at conferences, seminars, job interviews); and
c) they will learn how to prepare a logic structure and be an authentic presenter with a strong delivery.
Course Program
Individual Performance and Assessment: Interest in developing further, being self-reflective, giving and receiving substantial feedback.
You’ll need to prepare a scientific presentation of 10 min length in English between the first and second day.
1 ECTS (30 learning hours)
Annually (Spring term)
Lecturer: Dr. Barbara Hellermann
This course is a foundation course in scientific writing skills. It offers writers practice in expressing themselves precisely, concisely and, above all, clearly when writing English for scientific purposes. Particular attention is paid to Organisation, Flow and Style. Participants will receive feedback on their writing and will have the opportunity to edit and improve texts written in English. The course serves as preparation for a second course, “Scientific Writing Practice 2: Writing Up Research in English”, which accompanies scientific writers as they produce the individual chapters of a research article in English.
Individual Performance and Assessment: Attendance and active participation during day 1 and day 2 (16 hours). In order to complete the course and gain their credit point, students will be required to complete a writing task between Day 1 and Day 2 of the course and submit it to the course instructor for evaluation (preparation work of 14 hours).
1 ECTS (30 learning hours)
Annually (Fall semester)
Lecturer: Dr. Patrick Turko, USZ
This course is tailored for PhD students working in life sciences, who wish to improve their writing skills in English. The course emphasizes the importance of simplicity, clarity, and brevity to communicate science in an effective manner. During the course, participants will develop a critical approach towards the recognition of elements that make written communication weaker or stronger. Participants will improve their self-confidence towards the writing of scientific manuscripts and the communication of science as a whole.
The course covers the following topics: 1) Grammar and syntax. Where to position different types of words (nouns, adverbs, etc.) within a sentence. The importance of punctuation, and its use in scientific writing to avoid ambiguity. Breaking up long sentences. The use of active and passive voices. Removing redundancy. How to connect sentences. 2) Avoid ambiguity and vagueness. The use of “which, who, that”. The use of “a, one, the”. Latin words and numbers.; 3) The structure of a paragraph. Where to put new and old information. Breaking up long paragraphs. Readability tests and the use of spell checkers.; 4) Sections of a scientific manuscript. The importance of figures to draw a story-line. The title. The abstract. How Hollywood movie industry can help scientists writing better abstracts. How to structure the introduction, methods, results, and discussion. Hedging and criticism.
Individual Performance and Assessment: Practical activities will be carried out during the course. Students will be requested to complete the assigned homework. Homework include grammar exercises, the writing of a short essay (e.g. in the style of a Nature commentary on a recent scientific discovery, or the Working Life column of Science), and the writing of a mini-paper. Successful achievement of the credit point is based on course attendance and completion of assigned work.
1 ECTS (30 learning hours)
Annually (Spring semester)
Lecturer: Dr. Jacopo Marino, Paul Scherrer Institute (PSI)
The first teaching experience should be effective, enjoyable, and personally beneficial. This course gives the basic knowledge, tools, and practice to have such an experience. Participants will learn to make scientific expertise accessible to students and build a repertoire of evidence-based strategies for teaching abstract science topics to students and making them active and successful learners. We will show how to communicate science to novices as well as advanced students in science.
Individual Performance and Assessment: The assignment must be completed to obtain 2 ECTS..
1 ECTS (30 learning hours)
Annually (Spring semester)
Lecturers: Sarah Petchey, UZH
tba.
Individual Performance and Assessment: tba
0 ECTS (30 learning hours)
Annually (NEW: Fall Semester 2022)
Lecturer: Aria Minder (ETHZ GDC) (UZH)
Research needs funding from third parties, mainly public funding providers. Postdocs are supposed to write research proposals to acquire funding for their research ideas and their team. But to successfully obtain these third-party funds it is essential to have an all-around convincing project proposal, which exposes the own research idea in a keen manner.
In this training, participants will step-by-step learn to design a research project and write specific parts of a research proposal: the research plan, the impact chapter, the implementation, the career plan, the budget, the ethics, the gender aspects and other parts requested by the funding agencies the participants intend to address. They will furthermore discuss communication issues and how our messages are transported effectively to evaluation committees, including the presentation of the research group and CVs. To distinguish proposal writing from scientific (paper) writing is of key importance and therefore, elements in common and differences will be elaborated.
Because the proposal writing process and the acquisition of funding remains a permanent task of university research staff, we will show how to streamline the creativity process and the proposal writing within the scientific workflow. We help you to make proposal writing an integrated, valuable, and pleasant activity!
Target Group: Researchers, having a first project idea and a target funding instrument in mind
Individual Performance and Assessment: ungraded semester performance. Course attendance and active participation: 16 hours. Preparation work and home work: 14 hours.
1 ECTS (30 learning hours)
Annually (Fall semester)
Lecturer: Dr. Andrea Degen, eurelations AG, Dr. Melanie Paschke
Digital technologies have been deemed as powerful tools for fulfilling the Sustainable Development Goals. However, technological innovation can intersect with values, norms, and moral commitments and thus fail environmental, economic or societal improvements. A responsible way forward considers values in the use and development of the technologies.
This course introduces the concept of value-sensitive innovation to inform students about the ethical considerations associated with the use and development of emerging technologies. It will equip young scientists with a value-based innovation approach, which they could bring with when they enter today’s increasingly digitalized society. It will transmit not only a body of knowledge, but as well a set of toolkits, to students to use in their own domains of research.
The blended-learning course with face-to-face block course elements, self-learning phases and case studies is at the intersection between technology ethics, value-based design and responsible innovation. Participants will prepare one design or innovation project, which they are currently, or might be in the future, working on. For more detail, please see course script.
Individual Performance and Assessment: Each block will include exercises and short presentations to be finished by participants. Self-learning material will be finished by self-test. Final day: Individual presentation of your ethically informed innovation or design strategy based on the framework and tools introduced in this course.
2 ECTS (60 learning hours)
Annually (NEW: Spring semester 2022)
Lecturers: Ning Wang (UZH) and Dr. Melanie Paschke, Zurich-Basel Plant Science Center
► This course addresses PhD and Master's students
3 ECTS (90 working hours)
Note: organized every two years – next 7.12.2022
Target group: PSC PhD Students
A group of 5-6 PSC PhD students will be responsible for the organisation of an international and interdisciplinary science conference. As a member of the scientific and organisation committee (OK), you will cover the following tasks:
• Setting the symposium topic
• Invite international speakers to contribute to a high-quality scientific program
• Organise symposium logistics
• Fundraising and finances.
Have a look at past PSC Symposia
If you are interested in joining the Conference Organizing Committee for the next symposium organised by PhD students, contact the PhD Program coordinator
Please register through Life Science Zurich Graduate School
Choice of courses offered
• Career Cornerstones -– Active Career Building in Academia and Business (1 ECTS, 2 full days / 24 learning hours), Dr. Monika Clausen, Dr. Monika Clausen & Netzwerkpartner GmbH (organized by LSZGS).
• Self-marketing Skills – Improve your International Presence (1 ECTS, 2 full days / 24 learning hours), Dr. Monika Clausen, Dr. Monika Clausen & Netzwerkpartner GmbH (organized by LSZGS).
• Competency Awareness – the Foundation of a Confident Self-Presentation (1 ECTS, 2 full days / 24 learning hours), Dr. Monika Clausen, Dr. Monika Clausen & Netzwerkpartner GmbH (organized by LSZGS).
• The Successful Start of a Business Career (1 ECTS, 2 full days / 24 learning hours), Dr. Monika Clausen, Dr. Monika Clausen & Netzwerkpartner GmbH (organized by LSZGS).
PSC aims to mediate additional tools at the interfaces between research, policy, and diverse stakeholders. Students can attend courses from our specialized PSC PhD Program in Science and Policy.
The PSC PhD Program in Plant Science also organizes courses in cooperation with:
Life Science Zurich Graduate School
URPP Evolution in Action (UZH)
Courses offered by the following organisations can be fully accredited:
• University of Zurich
PhD students at Uni Basel have to register first at UZH for Module Mobility
PhD students at ETHZ have to register first at UZH as:
Special student "University of Zurich (UZH)"
• Hochschuldidaktik at University of Zurich Didactica
Graduate Campus (GRC, UZH), first register for Module Mobility!
• ETH Zurich:
PhD students at Uni Basel have to register first at ETHZ as:
Special student "University of Basel (UBa)"
PhD students at UZH have to register first at ETHZ as:
Special student "University of Zurich (UZH)"
• University of Basel GRACE
Excellent English language skills are a core requirement for a successful completion of the PSC PhD Program in Plant Sciences. University of Zurich and ETH Zurich offer language training.
(1 ECTS), Christian von Mering, Andreas Wagner, Kentaro Shimizu, UZH
In this course, the theoretical and practical aspects of sequence alignment, phylogeny reconstruction, genome-wide association of phenotypes and genotypes, and more was studies. In doing so, students learned how to generally manipulate data and launch software from the command line, including.
The course offers an opportunity to Swiss-based students to apply their knowledge and challenge their preconceptions to novel socio-environmental situations. The course specifically encourages students to explore and evaluate alternative management approaches that seek to integrate local economic needs with conservation priorities. An understanding of changing human perspectives to conservation (and associated land management approaches) will be gained. Using this understanding students will consider future challenges to conservation and land management, and develop solutions to resolve them.
The course will allow students to learn about ecology, conservation and management issues in a unique landscape. Daily excursions will focus on specific important issues relating to conservation management in the area. Excursions will be led by local experts representing science, management and policy, each of whom will explore with the students the complexities of the chosen topics. Topics will encompass species, habitats and landscapes from economic, ecological and cultural perspectives across various spatial and temporal scales.
Students will be encouraged to explore selected topics in more detail, examples being (1) trade-offs between deer, that are important to the local economy, and the regeneration of Caledonian pine forests, (2) the implications of changing land use and land-tenure systems, (3) the management of tourism on sensitive upland habitats, (4) securing a balance between renewable energy generation (e.g. wind farms, forestry) and landscape beauty, (5) predicted effects of climate change on plant communities, and (6) the impact of invasive species on natural plant communities.
In the evenings, group presentations and discussions based on the accumulated knowledge will aim to develop feasible solutions to current conservation challenges.
3 ECTS (90 learning hours)
Every second year (last 2017), next dates are not available
Lecturer: Prof. Jaboury Ghazoul, ETH Zurich
This class provides students with an overview of techniques for data analysis used in modern ecological research, as well as practical experience in running these analyses with R and interpreting the results. Topics include linear models, generalized linear models, mixed models, model selection and randomization methods. Students will be able to: - describe the aims and principles of important techniques for the analysis of ecological data; - choose appropriate techniques for given problems and types of data; - evaluate assumptions and limitations
- implement the analyses in R; - represent the relevant results in graphs, tables and text; and to interpret and evaluate the results in ecological terms. Course Contents will address: - Linear models for experimental and observational studies; - Model selection; - Introduction to likelihood inference and Bayesian statistics; - Analysis of counts and proportions (generalised linear models); - Models for non-linear relationships; - Grouping and correlation structures (mixed models); and Randomisation methods.
Individual Performance and Assessment: Graded semester performance.
1 ECTS (30 learning hours)
Annually (Fall Semester)
Lecturer: Dr. Sabine Güsewell
(1 ECTS), Prof. Thomas Boller, University of Basel
The aim of this course is to present an introduction to and overview of theory and experimental approaches to investigate "innate immunity" in plants. Recent work has shown that innate immunity in plants and animals are based on similar basic principles. In particular, both plants and animals recognize so-called "pathogen-associated molecular patterns" (PAMPs). These PAMPs elicit a defense response including formation of reactive oxygen species and induction of a multitude of genes.
(3 ECTS), Prof. Emmanuel Frossard, ETH Zurich
Radio-isotopes are extensively used at the soil/plant or ecosystem level to quantify the fluxes of elements (phosphorus (P), heavy metals, radionuclides) within a given system and to assess the importance of processes controlling these fluxes (e.g. exchange reactions between the soil solution and the soil solid phase, element turnover through the microbial biomass, organic matter mineralization etc.).
The course will first present the principles, the basic assumptions and the theoretical framework that underlay the work with radioisotopes. It will present how the introduction of an isotope into a system can be done so as to get information on the structure of the system (e.g. number and size of compartments). Secondly, case studies on isotopic dilution and tracer work will be presented for instance on the isotopic exchange kinetics method to determine nutrients or pollutants availability. The case studies will be adapted to the ongoing research of the group of plant nutrition and will thus give an insight into our current research. In addition, published studies will be analyzed and presented by the students. Finally, the advantages and disadvantages of work with radioisotopes will be analyzed and discussed critically.
This course provides an introduction to statistics ideal for MSc and PhD students in ecology or related fields. Of course, molecular biologists with an interest in statistics are welcome to join as well. Topics treated in this course include: important probability distributions, classical statistical tests (t-test, chi-square-test, U-test), the theory of hypothesis testing (examples: randomisation test and t-test, analysis of variance ANOVA, linear regression (simple and multiple), analysis of covariance ANCOVA, outlook, e.g. GLMs, MEMs. The course will consist of both lectures and computer practicals using the free software package R for statistics and graphics. Participants can bring their own PC or Mac laptops with the latest version of R downloaded from http://stat.ethz.ch/CRAN/ (a small number of computers will be available for those without laptops). The course will be limited to 20 people to allow one-to-one supervision during the computer practical exercises. Prerequisites: Knowledge of the R (or S-Plus) language would be ideal, but is not essential.
Individual Performance and Assessment: Attendance and active participation in the course (16 hours). In order to obtain the credit points, participants are required to hand in an assignment to be carried out at home. The details will be explained during the course. The assignment is due no later than one week after the course has ended. Preparation work for the assignment is 14 hours.
1 ECTS (30 learning hours)
Biannually (last 2018)
Lecturer: Dr. Stefanie von Felten, oikostat GmbH
The course introduces the study of plant genetic diversity and adaptation using population genomics approaches. Instructor will provide hands-on introduction to data handling, data exploration with summary statistics and data analysis with state-of-the art methods for demographic analysis, population differentiation and selection detection of plant populations. Each topic will be introduced with a conceptual lecture and discussion of recent literature. Students should complete the course with a good understanding of both underlying theory of the most important concepts and practical analysis experience that will enable them to apply these or similar methods to their own research. The data analysis part will use small datasets or the participant’s own data (after consultation with lecturers).
If the corona situation permits, the course will be taught in presence mode or alternatively, as online course.
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the 3 course days. Evaluation will be based on a written report that describes the analysis of the given dataset and discusses the result.
1 ECTS (30 learning hours)
Irregular (next 2020)
Lecturer: Prof. Dr. Karl Schmid and Dr. Fabian Freund, University of Hohenheim
What is a patent? How is it obtained? What are the implications of Life Science patents for – my career perspectives? – academic research? – society?
1 ECTS (30 learning hours)
Biannually (last 2018)
Lecturer: Prof. H. Müller, University of Basel et al. (organized by Life Science Zurich Graduate School.
NOTE: Please register through Life Science Zurich Graduate School: http://www.lifescience-graduateschool.uzh.ch/en/courses/tsc.html
During this capacity building workshop, students will be introduced to the concept of Open Data, Fair Data Principles and Standards, alongside the Open Data Repositories at EU, UZH and ETHZ. Moreover, they will familiarise with a list of key considerations for putting together an Open Data Strategy for their research results. This includes putting together a data management plan, data ecosystem mapping and consultancy for creating data ecosystems for agricultural programmes, building and working with data sharing agreements, data inventories and data trusts. The course includes theoretical input, workshops, consultancy, group and cases study work for data from the following areas: agricultural data, data from breeding research, isotope analysis data.
Individual Performance and Assessment: The following two tutorials should be finished within the course as self-study: The open innovation accelerator (2 hours); the open access author (2 hours). Please register at https://www.fosteropenscience.eu/learning-paths, choose the tutorials and provide the badges that you will get at the end of these tutorials to Romy Kohlmann (romy.kohlmann@usys.ethz.ch).
Additionally, on day 3 of the course there will be a presentation of the group works including the data management plan and the data ecosystem of your own research data.
1 ECTS (30 learning hours)
Last 2020, next to be defined
Lecturer: Violeta Mezeklieva, Data Trainer, Open Data Institute, London UK Stefanie Strebel, Data Services & Open Access, University of Zurich Melanie Paschke, Zurich-Basel Plant Science Center, ETH Zurich
Molecular data provide rich information about the biological forces shaping biodiversity. Molecular phylogenies are now routinely used to test a variety of biological hypotheses, with applications ranging from medicine and epidemiology to agriculture and ecology. Natural selection is one of the major forces shaping the genomic diversity, often responsible for adaptations to new pathogens and environments. This course will provide an introduction to modelling the molecular evolution, phylogeny inference and statistical hypothesis testing in phylogenetics. These techniques became a must in most genomic analyses. Models of sequence substitution, Inferring phylogenies in a nutshell, Detecting positive selection at the protein coding level.
Individual Performance and Assessment: Project-based individual assignment, which should be submitted within 1 week after the course.
1 ECTS (30 learning hours)
Triannually (last 2019)
Lecturer: Dr. Maria Anisimova, ZHAW
Tba.
Individual Performance and Assessment: tba.
1 ECTS (30 learning hours)
Annually (NEW: Fall Semester 2022)
Lecturer: Prof Dr. Anne Roulin (UZH)
The fluxes that flow through the plant metabolic network sustain life and are directly linked to the agronomically important parameters of crop yield and composition. Flux is the only direct measure of metabolic activity, and so measurements of metabolic flux allow the definition of metabolic phenotypes that are closely related to biological function. An understanding of these phenotypes and the flux distributions that define them is therefore essential for analysis of the behavior and regulation of the plant metabolic network. This course provides a theoretical and practical introduction to the methods available for measuring, inferring or predicting fluxes and considers how this knowledge informs our understanding of the function of the plant metabolic network. The course will describe the methods used for the prediction and measurement of fluxes in the plant metabolic network. It will provide an assessment of the applicability of these methods and a discussion of the significance of the results that have been obtained. This will include an analysis of the contribution of these methods to our understanding of the network as well as a discussion of the relevance of the methods to plant metabolic engineering. The lectures will be complemented by computing sessions that will introduce some of the modelling software used to analyse fluxes, providing an opportunity to explore the complex (and often counter-intuitive) behavior of metabolic networks.
Individual Performance and Assessment: Participants will be assessed on the basis of their contribution to the practical exercises that are integral to the course.
1 ECTS (24 learning hours)
Biannually (last 2018)
Lecturer: Prof. R. George Ratcliffe, Dr Nicholas J. Kruger, Department of Plant Sciences, University of Oxford, UK
(1 ECTS), Prof. Enrico Martinoia, University of Zurich
Life exists due to barriers established between the environment and the cell. Biological membranes establish these barriers. The lipid bilayer does not allow hydrophilic molecules such as ions and sugars to cross the membrane. On the other side, proteins embedded in the lipid bilayer are responsible for the selective uptake of constituents into the cell. Within eukaryotic cells compartmentation allows that different processes can occur at the same time in a cell. In this course we will show some techniques, how fluxes between the outside and within the cell can be measured. We will perform classical flux analysis using radiolabelled compounds with yeasts and protoplast and use the patch clamp technique to demonstrate ion currents across the vacuolar membrane.
Utilization of non-human biological material that comes from abroad is more than just a matter of competence in research techniques and methods. Scientists must be aware of legal and procedural requirements in order to correctly access biological material and to respect existing international and national regulations on plant genetic resources. Researchers need to be familiar with the Nagoya Protocol and terms such as Prior Informed Consent, Mutually Agreed Terms, Benefit-Sharing and Due Diligence in research. The overall goal of this course is to inform young scientists about the relevant international treaties and existing international and Swiss regulations that affect research projects with genetic resources and to illustrate which steps to undertake.
Training will focus on the a) Nagoya Protocol on Access to Genetic Resources and Benefit Sharing (ABS) and the Convention on Biological Diversity (CBD), b) International Treaty on Plant Genetic Resources for Food and Agriculture (IT FAO), and c) Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The course will provide solid knowledge on a) Correct and legitimate access to genetic resources and benefit-sharing for academic research,b) The Multilateral System of the plant treaty (ITPGRFA), c) Requirements for importing material under CITES in general, and specifically for plant genetic resources, and d) Swiss regulations, and available support and counseling services for scientists in Switzerland.
Individual Performance and Assessment: Participants are expected to submit a project description of their research project before the course starts.
1 ECTS (30 learning hours)
Biannually (last 2017)
Lecturer: Dr. Susette Biber-Klemm, SCNAT & University of Basel; Sylvia Martínez M.Sc., Univ. of Basel & Zurich-Basel Plant Science Center
(2 ECTS) Prof. Nina Buchmann, Dr. Rolf Siegwolf, ETHZ
This course provides an overview about the applicability of stable isotopes (carbon 13C, nitrogen 15N, oxygen 18O and water 2H) to process-oriented ecological research. Topics focus on stable isotopes as indicators for the origin of pools and fluxes, partitioning of composite fluxes as well as to trace and integrate processes. In addition, students carry out a small project during lab sessions. Learning Objective: Students will be familiar with be familiar with basic and advanced applications of stable isotopes in studies on plants, soils, water and trace gases, know the relevant approaches, concepts and recent results in stable isotope ecology, know how to combine classical and modern techniques to solve ecophysiological or ecological problems, learn to design, carry out and interpret a small IsoProject, practice to search and analyze literature as well as to give an oral presentation. Content: The analyses of stable isotopes often provide insights into ecophysiological and ecological processes that otherwise would not be available with classical methods only. Stable isotopes proved useful to determine origin of pools and fluxes in ecosystems, to partition composite fluxes and to integrate processes spatially and temporally.
(1 ECTS), Dr. Melanie Paschke, PSC
Online publishing and communicating has become an important channel for scientist to make their research visible, connect with other scientists, and open science to the interested public. Several technologies have popped up in recent years that can support scientists in their publication, communication and self-marketing purposes: open-access journals, research blogs and portfolios, research wikis and professional online networks.
In this two-day workshop, you will learn:
Topics discussed will include:
(1 ECTS), Luc Henry, Syngenta Basel, Switzerland
Currently, there is a remarkable gap between public perception and understanding of world agriculture and its role in our society. This places enormous stress and tension not only on governments and agribusinesses, but also on individuals as consumers. This gap, unfortunately, is widening and future opinion leaders have a major role to play in filling this gap. The objective of this course therefore is to provide students with the opportunity to explore the topic of world agriculture (including production and consumption, the technologies used and being developed, the impact on the environment, the food security challenge, the carbon footprint of agriculture, the biofuels, etc), and to put in place a framework to understand and foresee the potential required changes over the next years. The purpose of the course, by its very nature, is not to provide a single, “correct” perspective about agriculture. Instead, it aims at making students aware of possible scenarios, the consequences of the different scenarios, and help them to shape their own vision of agriculture in 2020.
(1 ECTS), Prof. Alex Widmer, ETH Institut für Integrative Biologie, Dr. Stefan Zoller and Dr. Jean-Claude Walser, Genetic Diversity Center, ETH Zurich
The goal of DNA barcoding is the identification of species through the analysis of nucleotide variation in short, standardized gene regions. These gene regions are typically amplified by PCR from samples of unknown origin and are then sequenced individually using standard Sanger sequencing technology. DNA metabarcoding is an extension that aims at identifying multiple species from a single, often complex and possibly degraded, environmental sample. A target gene region from all species represented in the sample is then amplified by PCR and sequenced using a high throughput nucleotide sequencing approach. DNA barcoding is widely used by ecologists and conservation biologists to identify species. Examples include the analysis of wood samples from logged trees or the validation of field identifications of vegetative plant parts. DNA metabarcoding is mainly used by ecologists and evolutionary biologists interested in biodiversity assessment, for example from water or soil samples, or the analysis of animal diet, gut bacteria composition and parasite diversity.
(1 ECTS), Prof. Beat Keller, University of Zurich
Genetic resistance is the most economical and environmentally friendly option for controlling plant diseases in agricultural ecosystems. Plant breeders have expended considerable effort to incorporate resistance genes into the major crops over the past 100 years. Pathogens have evolved to overcome many of these resistance genes, leading to a cycle of boom-and-bust with significant economic and societal consequences. This course will explore the molecular basis of disease resistance with an emphasis on agricultural crops. Topics will include: mechanisms of resistance; major gene resistance and quantitative resistance; genetic and biochemical models of gene-for-gene interactions; resistance gene structure and evolution; effector molecules in pathogens, boom-and-bust cycles and durable resistance; resistance gene deployment and management strategies; approaches for genetic engineering of resistance; identification and mapping of major resistance genes and quantitative (QTL) resistance; bioinformatics of plant pathogen genomes (“Pathogenomics”).
(1 ECTS) Prof. Antoine Guisan (U Lausanne), Prof. Niklaus E. Zimmermann (WSL, ETHZ), Prof. Yvonne Willi (U Basel)
The course will be based on a mix of lectures and practicals. The lectures will cover the preparation of data (species data and environmental predictors) for modelling, an introduction to basic and more advanced SDM fitting (e.g. GLM/GAM, CART, and their bagging/boosting versions) and evaluation methods, and how to derive projections to the same or different study areas, or to different time steps, such as future climates. The use of ensemble of models to assess uncertainty will also be covered. Practicals will allow the students to get trained in all these aspects. Due to the limited number of days (2), only an overview of these different aspects will be given and short practicals conducted. Depending on the course progress, there may be scope for individuals to work on their own data sets, so participants are encouraged to prepare their datasets as [species x sites] and [environment x sites] matrices before the course.
(1 ECTS), Prof. Nina Buchmann, Prof. Emmanuel Frossard, Prof. Johan Six, Dr. Roland Werner, Dr. Matthias Barthel, Dr. Charlotte Decock (ETH Zurich) and Prof. Ansgar Kahmen (University of Basel). Scientists at both field sites (DOK trial: Dr. Paul Mäder, Dr. Andreas Fliessbach (FiBl), Juliane Hirte (Agroscope); Hofstetten crane: Ansgar Kahmen)
Lectures: Introduction to stable isotopes, tracer vs. natural abundance applications, instrumentation. Overview lectures on stable carbon, nitrogen, oxygen and hydrogen isotope applications in agricultural and forest ecosystem sciences. Field visit: Students will get to know stable isotope applications in agricultural (DOK trial) and forest (Hofstetten crane site) ecosystems, interact with those who had carried out different stable isotope studies at the sites. Students know the basics about stable isotope applications to study plant and soil related research questions. Students are able to decide on tracer vs. natural abundance designs for a given research objective. Students understand the main mechanisms and processes imprinting on the stable isotope composition of the material of interest (e.g., plants, soils, gases).
Phylogenetics and phylodynamics are central topics in modern biology. Phylogenetic inferences reconstruct the evolutionary relationships between organisms, whereas phylodynamic inferences reveal the dynamics that lead to the observed relationships. These two fields have many practical applications in disciplines such as epidemiology, developmental biology, paleontology, ecology and even linguistics. However, phylogenetics and phylodynamics are complex and fast-evolving fields. As such, inference tools are not easily accessible to researchers who are not from a computational background. Taming the BEAST is a summer school focusing on the BEAST 2 software and consisting of a mix of invited talks, lectures and hands-on tutorials by leading and renowned experts in the field (including several of the core developers of BEAST 2). The aim of this summer school is to equip participants with the skills necessary to confidently perform their own phylogenetic and phylodynamic inferences in Bayesian settings, while providing them with a firm grasp of the theory behind those inferences. Participants are also highly encouraged to bring their own datasets along and to engage with the organizers and speakers to address any problems specific to their own datasets/analyses.
Individual Performance and Assessment: Students are required to complete all tutorials assigned during the workshop in order to receive course credit.
2 ECTS (60 learning hours)
last 2021, next to be announced
Lecturer: Dr. G. Singh Bhullar, FIBL; Dr. Franz Bender, Agroscope; Dr. Frank Liebisch and Dr. Melanie Paschke, ETH Zurich
