Postdoc: Data Science & Predictive Modelling for Potatoes

Admin; Vaud; On-site; CHF 100,000 - 130,000; Full time

Benefits offered by this job

Working for Switzerland

Embracing diversity

Staying healthy at work

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Machine learning

Predictive modelling

Statistical analysis

Python/R

Explainable AI

Geospatial data knowledge

Education

PhD in Data Science or related field

Job description

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.