Postdoctoral Researcher in Data Science and Predictive Modelling for Potato Production Systems

Admin; Vaud; Presencial; CHF 100 000 - 130 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Working for Switzerland

Embracing diversity

Staying healthy at work

Resumo da oferta

Agroscope, the Swiss federal centre of excellence for research in agriculture and food, invites applications to contribute to machine learning models predicting virus infection risk in seed potato production and to develop decision-support tools within Agrometeo+ and other platforms.

Collaborate with multidisciplinary teams, supervise MSc/PhD students, publish research, and present at international conferences while advancing datasets spanning more than 30 years.

Qualificações

• PhD in Data Science, Statistics, Computer Science, AI, Bioinformatics, Agronomy or related field.
• Strong expertise in machine learning, predictive modelling and statistical analysis.
• Excellent programming skills in Python and/or R, with experience handling large datasets and reproducible workflows.
• Knowledge of explainable AI, climate or geospatial data is advantageous.
• Excellent communication and scientific writing skills.
• Very good knowledge of two official Swiss languages and English.

Responsabilidades

• Develop ML and statistical models to predict virus infection risk in Swiss seed potato production.
• Integrate agronomic, climatic, physiological and certification datasets spanning 30+ years.
• Validate and optimize models using independent datasets and real-world observations.
• Develop decision-support tools and contribute to implementations on Agrometeo+ and other platforms.
• Publish scientific papers and present results at international conferences; contribute to proposals.
• Collaborate with multidisciplinary teams and supervise MSc/PhD students where appropriate.

Conhecimentos

Machine learning

Predictive modelling

Statistical analysis

Python/R

Explainable AI

Geospatial data knowledge

Formação académica

PhD in Data Science or related field

Descrição da oferta de emprego

This is how you can contribute

• Develop machine learning and statistical models to predict virus infection risk in Swiss seed potato production and predictive models of potato dormancy and sprouting under different storage conditions
• Integrate agronomic, climatic, physiological and certification datasets spanning more than 30 years
• Compare, validate and optimize predictive models using independent datasets and real-world observations
• Develop decision-support tools and contribute to their implementation within Agrometeo+ and other digital platforms
• Publish scientific papers, present results at international conferences and contribute to research proposals
• Collaborate with multidisciplinary teams and supervise MSc and PhD students where appropriate

This makes you unique

• PhD in Data Science, Statistics, Computer Science, Artificial Intelligence, Bioinformatics, Agronomy or a related field
• Strong expertise in machine learning, predictive modelling and statistical analysis
• Excellent programming skills in Python and/or R and experience with large datasets and reproducible workflows
• Knowledge of explainable AI, climate or geospatial data is an advantage
• Excellent communication and scientific writing skills
• Very good knowledge of two official Swiss languages and spoken and written English

Our benefits

• Working for Switzerland We are committed to the successful Swiss model and work for the public good.
• Embracing diversity Thanks to equal opportunities, we draw on our expertise and contribute different perspectives.
• Staying healthy at work We support and advise our employees in the area of physical and mental health.

Good food, healthy environment

Agroscope is the Swiss federal centre of excellence for research in the agriculture and food sector. Its researchers work at a number of sites in Switzerland. Headquartered in Bern-Liebefeld (as of 2026: Posieux), Agroscope is attached to the Swiss Federal Department of Economic Affairs, Education and Research EAER.