PhD Position: Statistical approaches to investigate and predict genomic vulnerability of populations and species, with applications to teosinte and maize.

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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

The goal of the PhD project is to contribute to the development of innovative Genome-Environment Association (GEA) and Genomic Offset (GO) procedures that will build on recent advances in optimization and statistical inference. More specifically the recruited PhD student will consider variational inference approaches for GEA and stochastic optimization to speed up the inference, with the objective of scaling up to modern genomic datasets that may involve hundreds of populations. He/she will also develop probabilistic GO models inspired from the Redundancy Analysis approach and extend it by introducing Neural Networks in order to handle non-linear relationships between covariates and response variables. To this aim, the PhD student will join a consortium of researchers issued from different disciplines with a long experience in interdisciplinary projects. The developed methodology will be applied to public datasets for benchmarking purposes, as well as, to an innovative set of two datasets corresponding to a domestic plant (maize) and its wild “ancestor” (teosinte). This will enable us to investigate how adaptation of crop wild relatives to dry environments could be informative about the response of maize to a drier climate.

The PhD will be hosted by the UMR MIA Paris Saclay, expert in statistical modeling and machine learning methodology with applications in genomics and genetics, and supervised by J. Aubert and T. Mary-Huard. 

Applications will be realized in collaboration with M. Tenaillon and L. Moreau, experts in quantitative and population genetics and maize breeding at UMR Génétique Quantitative et Évolution-Le Moulon.
The PhD student will also benefit from the co-supervision of Mathieu Gautier (CBGP, Univ Montpellier) for the development of GEA approaches.
The PhD is co-funded by the CLand project and the PEPR Maths-Vives.

Training and skills

The PhD student will be affiliated to the Graduate School “Ecole Doctorale de Mathématiques Hadamard” of Université Paris-Saclay.
The requirements are the following:

• A Master’sdegree in Applied Mathematics / Statistics / Machine Learning,
• Advanced programming skills in Python and/or R,
• Prior experience in biostatistics and genomic data analysis is desirable but not
  essential.

A strong interest in applications in biology and ability to work in a multidisciplinary team.

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