Junior research scientist in modelling for genomic prediction using complex data

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INRAE presentation

INRAE, the French National Research Institute for Agriculture, Food, and Environment, is a public research organization bringing together 12,000 employees across 272 units in 18 centers across France. As the world’s leading institute specializing in agriculture, food, and the environment, INRAE plays a key role in supporting the necessary transitions to address global challenges.

Faced with population growth, food security challenges, climate change, resource depletion, and biodiversity loss, INRAE is committed to developing scientific solutions and supporting the evolution of agricultural, food, and environmental practices.

INRAE is recruiting researchers by open competition and offering permanent position.

Work environment, missions and activities

You will join the Genetics, Physiology and Livestock Systems (GenPhyse, about 150 permanent staff) joint research unit, where researchers aim to contribute to the agroecological transition of livestock systems through better understanding of livestock biology, genetic bases of traits, and selection schemes to achieve resilient populations. The unit brings together skills in biology, physiology, genomics, genetics, statistics, and bioinformatics. Within the unit, you will join the Chamade team (Characterization and management of genetic diversity) of the Diversity and Selection group comprising methodologists in quantitative genetics (genomic prediction, selection and evolution) and population genomics, as well as statisticians.
Within your research team, you will be in charge of developing a new research programme in applied statistics to integrate high-throughput, heterogenous, and multiscale data into genetic and genomic evaluation methods. You will conduct your research to improve genomic prediction models by integrating new information relative to genome function (e.g. functional annotation), molecular phenotypes (e.g. transcriptomics, methylation), and high-throughput or intermediate phenotypes (e.g. longitudinal data, high throughput sensors).
To integrate different types of data into current genomic prediction models, you will draw on a variety of statistical modelling, for example modelling SNP effects according to their functional annotation category, or including random effects capturing the inter-individual covariance for intermediate phenotypes. The modelling could draw, for example, on hierarchical models, meta-analysis methods, mediation analysis or machine learning, possibly simulation-based. In addition, as new high-throughput data may not necessarily be available on the same individuals as traditional data, their integration will require the implementation of suitable statistical techniques. The predictive performance of the developed models will be evaluated using numerical simulations, for instance based on real breeding programmes. The models will also be tested on real data from experimental and commercial programmes of livestock species. These data will be available through existing projects and partnerships within the unit and the division to initiate your research project.
Computational efficiency must be taken into consideration in your developments to ultimately ensure their practical use in genetic and genomic evaluation. To develop your research, you will benefit from the proximity of experts in statistics, computer science, quantitative, molecular and population genetics within GenPhySE. In accordance with INRAE's policy for open science, in addition to scientific publications, you will promote your work by distributing free software implementing the new methods developed to ensure their wide dissemination to the international community.

Training and skills

Competition open to candidates with a PhD (or equivalent)
With a PhD in quantative genetics or applied statistics, you have very knowledge on genomic prediction methods and their theoretical background. You know how to program innovative prediction models and test them by explicit simulations of breeding programs. The disciplinary core of the job is quantitative genetics but it is expected that you will be able to understand works done by a large panel of collaborators in other academic fields (population genetics, statistics, molecular genetics) and by specialists of the animal breeding sector in order to identify and anticipate new opportunities arasing from those disciplines and the associated methodological challenges.
English fluency is required. A long term international experience is expected. In case the successful candidate does not have one, they will need to spend some time abroad upon hiring.

INRAE's life quality

By joining our teams, you benefit from:

- 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.

For international scientists: please visit your guide to facilitate your arrival and stay at INRAE. 

How to apply

1. I download the applicant guide Guide for applicants 2026 pdf - 1.41 MB
2. I write down the profile number CR26-GA-1
3. I apply GO