Job siteWelcome

You will work within the TIMC Laboratory (Translational Research and Innovation in Medicine and Complexity), a joint research unit (CNRS, UGA, G-INP, VetAgro Sup) comprising nearly 300 members, including 70 PhD students across 10 teams. TIMC drives innovative projects by placing translational research at the heart of its activities, thanks to close collaboration with Grenoble University Hospital (CHU). As a key player in innovation, the laboratory addresses societal needs and valorizes its research through the creation of start-ups. TIMC offers a stimulating interdisciplinary environment where clinicians and researchers collaborate on the application of computer science and applied mathematics in biology and health. You will thrive in a rich, collaborative, and supportive professional setting, benefiting from personalized guidance throughout your journey. Committed to equality and diversity, the laboratory is located on the Grenoble University Hospital’s health campus, providing a stimulating scientific environment and an excellent quality of life in the heart of the mountains.

Under the supervision of the leaders of the Computational Biology Group (compBio@TrEE), Nelle Varoquaux and Sophie Abby, and under the direction of the team leader, Fabien Pierrel, you will join the interdisciplinary TrEE team. This team brings together biochemists, molecular microbiologists, geneticists, biostatisticians, and bioinformaticians to study microbial evolution. You will work in close collaboration with the members of the TrEE team and the compBio@TrEE group, which currently includes two researchers, six PhD students, one postdoctoral fellow, and one bioinformatics engineer.

• Develop tools for annotating bioenergetic metabolic pathways in prokaryotic genomes by integrating comparative genomics and sequence/structure similarity search tools.
• Propose predictions to complete biosynthetic pathways of interest that may lead to experimental validation within the team and through collaborations.
• Investigate the evolution of bacterial and archaeal energy metabolism using phylogenomic approaches.
• Collect reference sequences for metabolic pathways to be annotated, from the literature and collaborators.
• Design and validate a strategy for annotating these metabolic pathways in genomes from public and private databases.
• Construct phylogenetic trees for bacterial and archaeal clades as well as for metabolic pathways of interest.
• Map annotation results onto these trees to interpret them and develop evolutionary scenarios.
• Communicate project progress and results through oral presentations or posters (internal meetings and conferences) and write scientific articles.

• Strong background and expertise in bioinformatics and sequence analysis.
• Proven skills in genome and metabolic pathway annotation.
• Proficiency in phylogenetics and comparative genomics.
• Programming skills in Python and bash/shell scripting.
• Familiarity with the Linux environment, computational servers, and version control tools (Git, GitHub, GitLab).
• Solid knowledge of prokaryotic metabolism and expertise in evolutionary genomics.
• Basic knowledge of structural biology, biochemistry, or machine learning is a plus.
• Collaborative mindset and ability to work in an interdisciplinary team.
• Scientific rigor, independence, and initiative.
• Strong oral and written communication skills for disseminating scientific work.

• Desired professional experience: 2 to 5 years.
• Preferred education/degree: PhD in bioinformatics or evolutionary microbiology.