Achim Walter

The Swiss Data Science Center (SDSC) at ETH Zürich is offering a postdoctoral position as part of the PhenoMix project, funded by the Swiss National Science Foundation (SNSF). This interdisciplinary project focuses on developing advanced machine learning and computer vision methods for automated plant phenotyping, with a strong emphasis on sustainable agriculture and crop science. The successful candidate will join a collaborative team spanning SDSC, the Crop Science Group (Prof. Achim Walter), the Grassland Sciences Group (Prof. Nina Buchmann), and AGROSCOPE (Dr. Susanne Vogelgsang), working at the intersection of data science, agricultural sciences, and environmental systems. The PhenoMix project leverages the Field Imaging Platform (FIP), a high-throughput phenotyping facility, and field experiments to generate multi-modal datasets of pure stands and crop mixtures. The postdoctoral researcher will develop novel data science tools for automated trait estimation, including foundation models for phenotyping, domain transfer methods, 3D reconstruction and rendering, human-in-the-loop approaches, and rigorous field evaluation. The role involves creating models that generalize across imaging platforms and environmental conditions, with real-world impact for farmers, breeders, and researchers. Key responsibilities include designing and implementing machine learning approaches for multi-trait plant phenotyping, developing domain-specific and physiologically plausible models, deploying active learning strategies, conducting field experiments, and generating comprehensive datasets for downstream analyses. The postdoc will also contribute to codebases, engage with open source communities, supervise students, and prepare scientific publications for top-tier venues. Applicants must have a PhD in computer science, machine learning, data science, or a relevant domain science, with demonstrated expertise in machine learning and computer vision. Required skills include proficiency in deep learning frameworks (PyTorch preferred), scientific programming in Python, experience with large multi-modal datasets, and excellent communication skills in English. Beneficial competencies include 3D reconstruction, active learning, Bayesian optimisation, and familiarity with agricultural sciences. The position is fully funded for up to 4 years, offering access to state-of-the-art phenotyping infrastructure, computational resources, and opportunities for professional development, including publishing research, presenting at international events, and supervising MSc and BSc students. ETH Zürich values diversity, sustainability, and work-life balance, providing a stimulating and inclusive research environment in Zurich. Applications must be submitted online via the ETH Zurich application portal. Required documents include a letter of motivation, CV with publication list, academic diplomas, transcripts, certificates, and contact details for 2–3 references. Links to code repositories or portfolios may be included. For questions regarding the position, contact Dr. Michele Volpi ([email protected]). Applications via email or postal services will not be considered. ETH Zürich is a world-leading university specializing in science and technology, renowned for its excellent education, cutting-edge research, and commitment to solving global challenges. The PhenoMix project offers a unique opportunity to contribute to the advancement of automated plant phenotyping and sustainable agriculture through innovative machine learning research.

The Crop Science group at ETH Zürich is offering a PhD position as part of the PhenoMix project, focusing on multidimensional field phenotyping of crop mixtures. Supported by the Swiss National Science Foundation, this position is embedded within a vibrant, interdisciplinary team in the Institute of Agricultural Sciences at the Department of Environmental Systems Science. The group’s research centers on developing methods and models to determine traits relevant for crop breeding and variety testing. PhenoMix is a collaborative project involving four research groups at ETH Zurich, the Swiss Data Science Center, and Agroscope. Its main goal is to leverage high throughput field phenotyping (HTFP) technology, plant physiological assessments, and data science to identify genotypes suitable for agroecologically beneficial legume-cereal mixtures. The project includes growing various pea, lentil, wheat, oats, and barley varieties under the field phenotyping platform FIP, on experimental and farmer’s fields. The PhD student will contribute to collecting HTFP data from devices such as multi-view RGB imaging systems, drones, handheld and manual devices. Responsibilities include designing and establishing a phenotyping robot capable of acquiring data from RGB cameras and other sensors, improving phenotyping workflows and models to extract traits like canopy height, cover, tillering, reflectance, senescence, and growth dynamics, and performing statistical analyses including AI-based approaches. The role also involves presenting results at national and international events, publishing in peer-reviewed journals, and assisting with plot establishment, maintenance, and harvest across all PhenoMix work packages. Applicants should have a Master’s degree in agricultural, data, or engineering sciences, or a closely related field. Experience with fieldwork, strong statistical skills, programming experience (R or Python), and proficiency in English are required. Good writing skills, a driver’s license, and the ability to work in an interdisciplinary team are expected. Experience in crop phenotyping and oral communication skills in German are beneficial. ETH Zurich offers numerous benefits, including public transport season tickets, car sharing, sports facilities, childcare, and attractive pension benefits. The university values diversity, sustainability, and an inclusive culture, promoting equality of opportunity and nurturing a fair environment for all staff and students. The position is full-time and funded for four years, with salary and social benefits provided according to ETH Zurich rules. The desired starting date is 1 August 2026. Applications must be submitted online by 15 May 2026, including a letter of motivation, CV, Bachelor’s and Master’s certificates with transcripts, a link to your MSc thesis, and contact information for two referees. For further information, contact Prof. Dr. Achim Walter at [email protected]. Only applications submitted via the online portal will be considered. ETH Zurich is a world-leading university specializing in science and technology, renowned for excellent education, cutting-edge research, and direct transfer of new knowledge into society. The university fosters independent thinking and inspires excellence, working together to develop solutions for global challenges.

This postdoctoral position in Phenotyping of Crop Mixtures is part of the PhenoMix project, supported by the Swiss National Science Foundation and hosted by the Crop Science group at ETH Zürich. The Crop Science group is an interdisciplinary team within the Institute of Agricultural Sciences at the Department of Environmental Systems Science. The PhenoMix project aims to advance multidimensional field phenotyping of crop mixtures, focusing on legume-cereal combinations such as pea, lentil, wheat, oats, and barley. The research leverages high throughput field phenotyping (HTFP) technology, plant physiological assessments, and data science to identify genotypes that can be successfully combined for agroecological benefits. The postdoc will coordinate overarching activities within the PhenoMix project, contribute to HTFP data collection, improve phenotyping workflows, and help develop a field robot for lean phenotyping. Responsibilities include co-designing and coordinating field experiments, collecting data from phenotyping devices (including multi-view RGB imaging, drones, handheld and manual devices), and generating modelling approaches to predict optimal crop combinations. The role also involves supervising and mentoring students from BSc to PhD level, assisting in lectures and seminars, publishing research in peer-reviewed journals, presenting at conferences, and contributing to international research networks. The initial contract is for two years, with the possibility of extension to the full four-year project duration based on performance. Salary and social benefits are provided according to ETH Zurich rules. Applicants must have a PhD in agricultural sciences or a related field, several years of research experience in field crop phenotyping, strong statistical and programming skills (R or Python), evidence of research excellence, and a strong desire for teaching and teamwork. A driver's license is required, and good oral communication skills in German are highly beneficial. ETH Zürich offers numerous benefits, including public transport season tickets, car sharing, sports facilities, childcare, and attractive pension benefits. The university values diversity, sustainability, and an inclusive culture. The desired starting date is 1 August 2026, and interviews will begin mid-May 2026. Applications must be submitted online via the ETH Zurich portal by 15 May 2026, including a letter of motivation, CV with publication list, academic certificates and transcripts, and two reference letters or referee contacts. For further information, contact Prof. Dr. Achim Walter at [email protected]. ETH Zürich is a leading university in science and technology, renowned for excellent education, cutting-edge research, and global impact. The Crop Science group and PhenoMix project offer a dynamic environment for impactful research in agricultural phenotyping and data-driven crop science.

This PhD position in Agro-Economic Analysis of Legume-Cereal Mixtures is part of the PhenoMix project, a collaborative research initiative supported by the Swiss National Science Foundation and hosted by the Crop Science group at ETH Zürich. The project aims to advance multidimensional field phenotyping of crop mixtures, focusing on the development of methods and models to determine traits relevant for crop breeding and variety testing. The research is conducted in partnership with Agroscope and the Swiss Data Science Center, integrating expertise from four research groups. The PhenoMix project investigates the hypothesis that high throughput field phenotyping technology, combined with plant physiological and ecosystem service assessments, can identify genotypes suitable for agroecologically beneficial legume-cereal mixtures. Field experiments will involve different varieties of legumes (peas, lentils) and cereals (wheat, oats, barley), grown in pure stands and mixtures on the Crop Science group's phenotyping platform, neighboring experimental fields, and farmers' fields. The project encompasses work packages in phenotyping, plant ecophysiology, data science, and agronomic-economic performance, with four doctoral students, two postdocs, and several technicians collaborating across these areas. The Agro-Economic doctoral student will play a key role in establishing and monitoring on-site and on-farm field experiments, assessing ecosystem services provided by lentil-cereal mixtures. Responsibilities include planning, conducting, and evaluating field and post-harvest laboratory experiments, performing statistical analyses (including AI-based approaches), presenting results at national and international events, publishing in peer-reviewed and practice-oriented journals, organizing national workshops for growers, the food industry, and consumers, and assisting in plot establishment, maintenance, monitoring, and harvest across all work packages. This full-time position is funded for four years, with salary and social benefits provided according to ETH Zurich rules. The place of work is Agroscope in Zurich-Affoltern. Applicants should hold a MSc degree in agricultural sciences, biology, ecology, or a related field, and demonstrate strong interest in applied interdisciplinary research, complex field experiments, and statistical analysis (e.g., R). Excellent written and spoken English, good writing skills, and a driver’s license are required. Experience in niche crops and oral communication skills in German are beneficial. ETH Zurich offers numerous benefits, including public transport season tickets, car sharing, sports facilities, childcare, and attractive pension benefits. The university values diversity, sustainability, and an inclusive culture, promoting equality of opportunity and a climate-neutral future. Applications must be submitted online by 31 May 2026, including a letter of motivation, CV, BSc and MSc certificates with transcripts, a link to the MSc thesis, and contact information for two referees. The desired starting date is 1 October 2026, with interviews beginning mid-June 2026. For further information, contact Prof. Dr. Achim Walter ([email protected]) or Dr. Susanne Vogelgsang ([email protected]). Applications via email or postal services will not be considered. ETH Zurich is a world-leading university specializing in science and technology, renowned for excellent education, cutting-edge research, and direct transfer of new knowledge into society. The university fosters independent thinking and inspires excellence, working together to develop solutions for global challenges.