Characterization of Microbial Consortia in Biomethanization Processes

• Evaluating the role of microbial diversity in the methanization performance of different internal blends
• Using state-of-the-art computational biology strategies (differential analyses, network modelling, metabolic pathways…) to focus on the in-depth evaluation of microbial interactions and their contributions to methane production efficiency
• Developing 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

• 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

• Join a family business rich in a long history with human-oriented values
• Evolve in an enriching work environment and a multicultural context
• Experience intellectual challenges within a multi-expertise network