Postdoctoral Researcher (24 months) – Hybrid Mechanistic & AI Modeling of Microbiomes

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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

You will build the computational backbone of a multi-scale modeling framework that links how individual bacterial strains metabolize plant matrices up to how whole microbial communities behave, so we can predict and steer which combinations of strains keep a targeted strain alive and active through fermentation.

Concretely, you will:

• Construct and curate genome-scale metabolic models (GEMs) for food-fermentation strains, using deep-learning-based reconstruction (e.g., DNNGIOR) and curated metabolic modules;

• Run static and dynamic flux balance analyses across thousands of simulated microbial consortia to prioritize strain combinations that support a targeted strain;

• Embed the resulting metabolic descriptors into a hybrid deep-learning model (compositional Neural ODEs) constrained by consumer–resource ecological equations;

• Combine scarce high-resolution experimental data with large public datasets and drive training with synthetic data from model forward simulations;

• Parameterize dynamic models with Physics-Informed Neural Networks (PINNs) to enforce biophysical constraints;

• Integrate an open multi-omics dataset with a validated predictive model to feed the project's digital-twin fermentation platform.

You will work at the interface of simulation and experiment, interacting closely with the wet-lab and digital-twin teams, with access to the MIGALE and Jean Zay computing clusters.

Training and skills

• PhD in systems biology, computational biology, bioinformatics, applied mathematics, biophysics, or equivalent;

• Strong mathematical/machine-learning skills: dynamical systems (ODEs, numerical simulation), deep learning (PyTorch/JAX or similar);

• Proficient Python development;

• Comfortable working in a multidisciplinary team and in English (French appreciated but not required).

Nice to have (any of):

• Genome-scale metabolic modeling / flux balance analysis (COBRApy or similar);

• Neural ODEs, PINNs, or hybrid mechanistic–ML models;

• Statistical analysis of large or genomic-scale datasets;

• Experience with microbial community or fermentation data.

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