Post-doctoral position: predictive modeling of malt quality starting from properties of barley

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

In the scope of the PROSIT-2 project, the candidate will work on real-world data coming from barely, collected over the course of several years. The objective is to develop interpretable, predictive machine learning models of the quality of malt starting from measurements of barley. 

The transformation process of barley into malt is extremely complex, including both chemical and mechanical steps, so it is notoriously difficult to characterize resorting to mechanistic models. The machine learning models will be validated by experts of the transformation process. 

The UMR MIA Paris-Saclay, associated with the supervisory bodies AgroParisTech, INRAE ​​and Université Paris Saclay, brings together statisticians and computer scientists specializing in statistical and computational modeling and learning for biology, ecology, the environment, agronomy and the agri-food sector. Their expertise covers statistical inference methods (complex models, latent variable models, Bayesian inference, learning, model selection, etc.) and algorithmic methods (generalization, domain transfer, knowledge representation). 

The EkINocs team's research activities are dedicated to data science methodologies, particularly machine learning and knowledge engineering, and to interactive modeling with experts in the fields studied.

Training and skills

PhD in computer science, applied mathematics, or other related discipline

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter