Postdoc position: spatial statistics and machine learning for choosing crop varieties

*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{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7}-100{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7}) 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:
david.ginsbourger@stat.unibe.ch

and Dr. Juan Herrera:
juan.herrera@agroscope.admin.ch