Internship 6 months : Characterization of Microbial Consortia in Biomethanization Processes (W/M)Lesaffre

As a global key player in yeasts and fermentation, Lesaffre designs, manufactures and markets innovative solutions for Baking, Food taste & pleasure, Health care and Biotechnology.

Family group born in northern France in 1853, now a multi-national and a multicultural company, Lesaffre is committed to working with confidence to better nourish and protect the planet.
In close collaboration with its clients and partners, Lesaffre employs 11 000 people in more than 50 countries.

Lesaffre achieves a turnover of 3 billion euros.

In the face of climate change, developing sustainable alternatives to fossil fuel-based gas production has become an urgent priority. Biomethanization — the transformation of organic matter through the metabolic activity of anaerobic microbial communities — holds a central role in this transition. This process generates biogas, a renewable energy source primarily composed of methane and carbon dioxide, which can be used for domestic and industrial heating.

At Phileo by Lesaffre we develop new microorganism-based solutions to promote animal well-being to support an economical and ecological substainable animal sector. Within this vision, the valorization of animal-derived products, such as animal waste for biomethane production presents an important opportunity to address ecological and economic challenges.

In collaboration with three corporate R&D departments (Biodata, Synthetic System Biology and Discovery Front-end Innovation) and one Business Unit (Phileo), the internship will consist of evaluating the role of microbial diversity in the methanization performance of different internal blends.

Internship Objectives

Using state-of-the-art computational biology strategies (differential analyses, network modelling, metabolic pathways…), the work will focus on the in-depth evaluation of microbial interactions and their contributions to methane production efficiency.

The candidate will develop robust and reproducible software tools (Python, R, CI/CD) to enable efficient exploration of results to provide actionable insights for industrial applications.

The valorisation of results through internal and external scientific communications is expected.

Candidate profile :

• Graduate student (M2 or Last year Engineering student) in bioinformatics, applied mathematics or statistics
• Proficency in standard statistical analyses (inferences in high dimensional data)
• Good programming skills in R and Python
• Good communication skills in both French and English to a large audience
• Curiosity and team spirit
• Interest in problem-solving within an industrial R&D setting
• Knowledge in microbial biology will be considered as an asset