Postdoc position: spatial statistics and machine learning for choosing crop varieties at Uni Bern
Postdoc position: spatial statistics and machine learning for choosing crop varieties
In the framework of the “Wheat Advisor” project coordinated by Swissgranum and involving various parties including researchers from the Swiss centre for agricultural research (Agroscope) and the University of Bern (UniBE), we are calling for applications for a postdoctoral position (80%-100%) to be funded subject to successful completion of the collaboration contract.
The main focus of this collaboration is to leverage recent progresses in statistical modelling and in machine learning to help more efficiently recommending which crop variety to choose in farms depending on measured and indirectly inferred co-variables.
Population growth and climate change increasing pressures on our global food systems call for a sustainable intensification of food production while increasing the systems’ resilience to climatic risks. Recommending crop varieties with optimum yield potential given a particular environmental setting and management is key to achieving these goals. However, evidence-based decision-support tools that could help farmers choose the most suitable crop varieties for their fields are lacking so far. This postdoc position addresses this gap via the investigation of different prediction approaches to optimize variety-specific wheat yields given information on local climate, nitrogen supply, soil and topography.
This endeavor is quite challenging as available data presents variability due not only to the latter co-variables but also due to climatic fluctuations, unobserved properties of individual crops, and more.
The aim of this position is to evaluate and develop novel approaches borrowing the best from both distance/kernel-based prediction and mixed effects statistical modelling for improving decision-making regarding which wheat variety to grow in specific environments and designing more efficient experimental networks. In particular, the recruited postdoctoral researcher will be involved in designing a campaign of novel crop experiments, hence going all the way from statistical modelling to experimental design, data collection, and ideally prototyping a recommendation tool for wheat producers. The outputs will hence provide valuable insights to increase both food security and the ecological sustainability of wheat production in Switzerland.
This work will be developed mainly through a collaboration between the Institute of Mathematical Statistics and Actuarial Science of UniBE and Agroscope at Changins. The ideal candidate is a statistician with a taste for large-scale agronomical applications or an agronomist with outstanding statistics skills. The position is for 1 year, with possibility of an extension on the project towards further practical implementations of the investigated and developed approaches in agronomical contexts. The starting date is as soon as possible in 2020. Applications will be reviewed swiftly and selected candidates will be contacted for interviews.
CV, publication list and motivation letter (with contact information of up to 3 persons accepting to be asked for recommendation letters) to be sent jointly to:
Prof. Dr. David Ginsbourger: email@example.com
and Dr. Juan Herrera: firstname.lastname@example.org