Research & Technical Skills

Technical and research skills of the program are developed in all areas from molecular biology to ecology and system approaches. The courses are developed to allow an understanding and mastering of relevant research methodologies and techniques and their appropriate application.

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Identification of plant diseases based on host, symptoms and pathogen micromorphology. The diagnostics part is completed with life cycles and related control measures for the most important fungal diseases of selected annual and perennial crops and their causal pathogens.

Course Program: 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.

Prior Knowledge: None

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
Annualy (Spring Semester)
Lecturer: Prof. Dr. Monika Maurhofer Bringolf
Location: ETH Zurich

Challenges in Plant Sciences – PSC Colloquium 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

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)
Lecturers: 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
Location: University of 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:

• Timing of key stages;
• Quantities at defined time points or periods and
• 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 (Spring semester)
Lecturers: Dr. Andreas Hund, Lukas Roth, Jonas Anderegg, Prof. Achim Walter, Jörg Leipner (ETHZ)
Location: ETH 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:

• Deepening of scientific knowledge in plant breeding
• Critical evaluation of current challenges and new concepts in plant breeding
• Promotion of collaboration and Master thesis projects with practical plant breeders

Soft skills:

• Independent literature research to get familiar with the selected topic
• Critical evaluation and consolidation of the acquired knowledge in an interdisciplinary team 
• Establishment of a scientific presentation in an interdisciplinary team
• Presentation and discussion of the teamwork outcome
• Establishing contacts and strengthening the network to national and international plant breeders and scientist

Individual Performance and Assessment: In the autumn semester, the course participating students are meeting with the lecturers as well as four to six tutors, selected according to their expertise in the selected topic (one afternoon, for about two hours). After an input talk by the lecturers, four to six specific questions/aspects are identified and phrased. The tutors and the enrolled students, assigned to four to six different groups, are critically evaluating one question/aspect of the selected topic. The students, guided by tutors, then prepare a presentation of 15 minutes (plus five minutes of discussion) covering their specific question/aspect.

After a preparation phase of around two months (including around 4-6 meetings within the group and the tutors), a whole-day seminar on the selected topic is organized. The presentations of the students are complemented with keynote talks from national and international experts, to discuss and critically evaluate the selected topic/area.

2 ECTS (60 learning hours)
Annually (Autumn semester)
Lecturers: Prof. Bruno Studer and Dr. Andreas Hund, ETH Zurich
Location: ETH Zurich

The course introduces imaging and spectroscopy techniques spanning spectral and spatial scales: from UV–visible and near-infrared to X-ray methods, and from microns to entire landscapes. Using ground, drone, and satellite platforms, students gain hands-on experience acquiring, processing, and interpreting data on soil and vegetation in environmental and agricultural systems.

In the first half of the semester, students are introduced to a series spectroscopy and imaging processing techniques. Each weekly module consists of a two-hour theoretical lecture establishing the scientific foundations of the method, followed by self-guided exercises (with dedicated support hours) focusing on data processing and analysis using real datasets drawn from the lecturers’ research.

Students progress from analysing individual spectra, to applying classical and advanced image processing techniques, through the following modules:

• The Leaf Spectrum;
• The Soil Spectrum;
• Imaging Spectroscopy: Classification and Temporal Change Analysis;
• Seeing Soil from the Sky: Remote sensing of soil properties;
• Deep Learning for Tree Species Identification;
• X-ray tomography: Image Segmentation of Soil Microstructure;
• Drone-based Imaging: from Canopy to Landscape Structure

In the second half of the semester, students work in groups on a project focused on one technique of their choice. They design and implement a sampling strategy, collect and acquire their own data in the field, and apply the analytical approaches learned earlier in the course. Building on these skills, they process, interpret, and critically discuss their results to address a specific research question.

The course is held at the ETH Eschikon-Lindau Campus, offering an immersive learning experience that combines classroom learning with hands-on field projects. The unique setting enables students to develop practical skills and apply the methods learned directly in both forest and agricultural systems.

Individual Performance and Assessment: PhD students will take part in the MSc course 701-1634-00L PReSens: Proximal and Remote Sensing for Soil and Vegetation. A reduced workload will allow to acquire 2 instead of the 5 ECTS points: Participants enrolled in the PSC are required to i) participate in the lectures, and ii) submit 4 of 8 exercises.
Participation in the group work conducted during the second half of the semester must be agreed with the lecturer on an individual basis at the beginning of the semester and may allow PhD students to acquire an additional 1 ECTS credit.

Prior Knowledge: There are no formal prerequisites. Students are expected to have a basic understanding of soil science, plant physiology, and data science, as well as a strong interest in developing practical skills for soil and vegetation monitoring. Prior experience with GIS, or completion of 701-0951-00L “GIS – Introduction into Geoinformation Science” (or an equivalent course), is an advantage.

2 ECTS
Annually (Spring semester)
Lecturers: Dr. Fanny Petibon, Dr. Mirela Beloiu Schwenke, Dr. Patrick Duddek
Location: 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 (Autumn semester)
Lecturers: Dr. G. Singh Bhullar, FIBL; Dr. Franz Bender, Agroscope; Dr. Frank Liebisch and Dr. Melanie Paschke, ETH Zurich
Location: 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
Location: ETH Zurich

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.

This course addresses the challenges of subcellular localization of fluorescent compounds in intact plant tissues and organs. Key issues include the high refractive index of fresh tissues, sample thickness, and stress-induced autofluorescence in dissected samples, alongside classical concerns such as photobleaching and phototoxicity. These factors complicate high-resolution and time-lapse imaging of fluorescent reporter proteins.
Participants will explore microscopy techniques tailored to specific applications, receive practical tips for optimizing imaging conditions, and engage in hands-on sessions with confocal laser scanning microscopy and multiphoton imaging. Emphasis will be placed on customizing acquisition parameters to achieve maximum resolution while balancing speed, viability, photobleaching, and signal diffraction in fresh versus fixed Arabidopsis tissues.
Additionally, the course will introduce image data management and analysis techniques, including 3D volume rendering, image segmentation, and quantitative information extraction for statistical analysis using tools like Fiji, Imaris, and Biom3D, an ML-based segmentation tool.

Course Program and Learning Objectives

Day 1 & Day 2: High-Resolution Imaging of fixed and fresh plant tissues

Lectures
Provide an overview of imaging strategies, theoretical considerations and references for further training
• Learn about different microscopy modalities for plant tissue imaging
• Learn about sample preparation strategies: clearing, staining, mounting
• Learn about Imaging Design: important considerations at sample preparation and acquisition for meaningful qualitative and quantitative analyses
• Lear about FAIR (Findable, Accessible, Interoperable, Reproducible) imaging
Hands-on sessions
Parallel imaging sessions using confocal laser scanning (incl. resonance and life-time spectral separation) and two -photon (deep tissue imaging) microscopy.
• Practice acquisition to balance speed, signal-to-noise ratio and resolution
• Learn about specific challenges and benefits of fixed vs fresh tissue samples

(Hands-on sessions do not provide an introductory training to these instruments –see requirements. Instead, practical imaging problems are presented, possible solutions are discussed with the participants and demonstrated).

Day 3 & Day 4: Image processing

Lectures
Provide an overview of image data management and image analysis strategies and references for further training
• Learn about image data management: goals, best practice and tools
• Learn about software solutions and resources for 3D image processing
• Lear about FAIR image analysis
• Example 1: Image analysis workflow using Imaris (Bitplane)
• Example 2: Image analysis workflow using Fiji
• Example 3: Image analysis workflow using Biom3D

Hands-on sessions:
Two consecutive sessions to learn the fundaments of Imaris, Fiji and Biom3D
• Learn to do 3D volume rendering and produce high-quality pictures for publication
• Learn to segment and extract quantitative measurements from 3D images: fluorescence intensity, number and geometric descriptors of cells or subcellular compartments.

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 participants have a good understanding of fluorescence microscopy and confocal imaging principles and have already practiced confocal imaging.
This course is not meant to provide an introduction nor first hands training on microscopy imaging (for this, see https://www.zmb.uzh.ch/en/teaching.html).

1 ECTS (30 learning hours)
Every three years (Spring semester)
Lecturer: Célia Baroux (UZH, Coordinator) and guest lecturer
Location: University of Zurich

This intensive 3-day workshop introduces PhD students to the fundamentals and practical application of crop modelling, with a strong focus on hands-on learning. Participants will explore key concepts of crop modelling for agro-climatic risk assessment and gain an in-depth understanding of the open-source CropSuite model framework. The course covers a detailed understanding of the required input data, model structure, and interpretation of model outputs, with practical exercises throughout. In the final hackathon-style day, students will work independently on an applied case study, implementing CropSuite to address a real-world research question. Results will be presented and discussed in a final group presentation, followed by an informal apéro.

Course Program and Learning Objectives
Fundamentals of crop modelling for agro-climatic risk assessment; Understanding the CropSuite modelling framework, the principles behind the approach and the required input data; Application of the CropSuite model and interpretation of model outputs.

Prior Knowledgestrong>
Participants should have MSc-level training in plant sciences or a related discipline. Basic knowledge of climate–crop interactions, statistics, familiarity with spatial climate datasets, and experience with programming (e.g., Python or R) is advantageous but not required.

1 ECTS
Lecturer: PD Dr. Florian Zabel (UNIBAS)
Location: University of Basel

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 
Lecturer: Dr Diana Santelia, ETHZ; Klára Panzarová, Photon Systems Instruments (PSI); Tracy Lawson, University of Essex (UK), Fiamma Longoni, University of Neuchâtel.
Location: 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
Location: 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.

2 ECTS (60 learning hours)
Annually (Autumn semester)
Lecturer: Dr. Aria M. Minder, ETH Zurich
Location: ETH Zurich

This course is a hands-on introduction to machine learning with Python for biologists with focus on genomics and evolution. It focuses on analyzing gene expression and experimental data. You will start with the basics, like preparing data and making graphs, then move on to practical tasks. Workflow of the Functional Genomics Center Zurich is used for the hands-on of next-generation sequencing data. We will also use Large Language Models (LLMs) as a powerful helper to make programming and data analysis easier.

By the end of the module the students should be able to:

• Understand concepts of NGS technologies
• Understand fundamentals of data analysis
• Design a research experiment and the data analysis involving biologically relevant issues affecting populations of plants or animals
• Run machine learning analysis process
• 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. Report at the final class will be required.

1 ECTS (30 learning hours)
Annually (fall semester)
Lecturers: Prof. Kentaro Schimizu, Prof. Dr. Jun Sese, Dr. Masaomi Hatakeyama, Dr. Rie Shimizu-Inatsugi, Dr. Narjes Yousefi, Dr. Claudio Quilodran Venegas
Location: University of Zurich

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
Location: 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
Location: ETH Zurich