Following recent investments in high-throughput microbial screening and genome editing platforms, the Lesaffre Institute for Science and Technology (LIST) seeks to expand its capacity in the fields of computational biology and artificial intelligence.

As a Computational Biology Research Scientist, you will join the Computation and Artificial Intelligence for Biology team, which is part of the BioData Center of Excellence. Our mission is to accelerate the development of Lesaffre products by leveraging multi-omics data and artificial intelligence. Our expertise spans diverse domains such as bioinformatics, comparative genomics and transcriptomics, metabolic engineering, high-dimensional statistics and deep learning. We act as an innovation enabler and catalyst, working in close collaborations with the various Business Units of Lesaffre and the other LIST Centers of Excellence, on a great variety of projects.

Missions:

As a Computational Biology Research Scientist, your role will be to:

• Work in close collaboration with wet-lab teams to define appropriate design of experiments, to ensure data traceability within the LIMS of the company, and to define quality control procedures for different omics modalities (genomics, transcriptomics, proteomics, metabolomics).
• Develop state-of-the-art know-how for the analysis of omics data, involving for instance GWAS and QTL campaigns, time-course transcriptomics data, or multi-omics data integration.
• Propose innovative metabolic engineering approaches to simulate cell metabolism and to optimize metabolic pathways.
• Rely on recent deep-learning advances to extract added-value information from Lesaffre proprietary strains collection, and to engineer proteins to maximize their activity.
• Contribute to the operational excellence of the LIST, by ensuring a timely delivery of results, a high-quality reporting of your contributions to projects and the valorization of your work by means of publications and patents.

For this position, we require:

• A PhD with ideally 3 years of experience in the field of computational / system biology, or bioinformatics.
• Strong experience in analyzing omics data.
• In depth knowledge of microbial biology and cell metabolism.
• Experience in statistical modeling, high-dimensional statistics, and data visualization.
• Good programming and development skills (R, Python, Unix / bash, Git, AWS, DevOps).
• Excellent communication and interpersonal skills.
• Aspiration for excellence and performance.
• Curiosity and team spirit.
• Fluency in English.

Prior experience in the following domains would be considered a plus:

• Industrial fermentation applications.
• Mass-spectrometry data analysis.
• QTL and GWAS analyses.
• Genome-scale metabolic models.
• Multi-omics data integration.
• Machine / deep-Learning.