Synthetic & Systems Biology Computational Scientist (H/F)

The Synthetic & Systems Biology team is part of the Bioengineering Center of Excellence and a core member of its Biofoundry. Our purpose is to design, build and learn from Lesaffre organisms, genes and genomes.

We have three core missions. First, we enable the large-scale, rational exploration of the strain design space by building arrayed strain libraries either for enzyme discovery, metabolic pathway optimization, hypothesis testing or gene target identification. Second, we combine high-content / genome-wide quantitative experiments and mathematical modeling to characterize and model strain (or strain consortium) behavior as a function of its genome (or their genomes). Finally, we provide access to a variety of full-stack NGS workflows tailored to needs of both the Lesaffre Institute of Science and Technology and Lesaffre Business Units.

Our team is already bringing together diverse expertises (in high-throughput synthetic biology and NGS, in computational biology and mathematical modeling…). We are now seeking a synthetic & systems biology scientist with computational skills to 1) contribute to our data analysis and experiment design efforts and 2) help us maintain and improve our data quality as we grow in scope and help us increase our throughput in both data generation and automated data analysis.

Missions :

As a member of the Synthetic & Systems Biology team, your role will be to :

• Contribute to strain development as well as method development projects
  • Analyse a diverse range of data (genomics, transcriptomics, physiological data from controlled fermentations, applicative performance data, other phenotypes from enzymatic, growth-based, cytometry-based assays…) to generate project-specific insights
  • Make recommandations on informative experiments or new computational analyses to perform in order to fill project-critical gaps in knowledge
• Unlock operational excellence in data generation and automated data analysis  
  • Develop a detailed, structured understanding of all our processes and workflows both in terms of physical world operations (transformation and transfer of samples),  of data flows (measurements, external information) and of their interdependence (sample tracking, quality control, decision branching points in protocols)
  • Challenge our current data model and workflow automation procedures both using a bottom-up approach (i.e. starting from identified structured issues bottlenecks, cost-suboptimal steps, weaknesses in quality control…) and a top-down approach (i.e. starting from design principles identified in de-novo system design efforts)
  • Participate in the implementation of the redesigned data model, processes and workflows by contributing to the associated codebase, re-configuring the LIMS (Laboratory Information Management System), and deploying necessary micro-services on our compute infrastructure
  • Establish good practices leveraging the LIMS for tracking the quality, time and cost efficiency tracking of the all the team workflows. Perform accurate simulations of potential workflow variations to score their potential
  • Grow and maintain knowledge and proficiency regarding relevant software programming and data engineering skills, by actively sharing your experiences within a community of Lesaffre developpers spanning a wide range of teams