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 bioinformatics.
As a Computational Biology Scientist you will join 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 Scientist your role will be to:
- Develop advanced data analysis methods for omics analysis:
- Devise state-of-the-art techniques for preprocessing quality control visualization and integration of data coming from different omics modalities (genomics transcriptomics proteomics metabolomics).
- Contribute to the development and implementation of best practices for high-dimensional statistical inference.
- Develop innovative prediction and analysis methods using genome scale models of metabolism:
- Contextualize the omics measurements using genome-scale models of metabolism
- Develop new metabolic engineering prediction methods
- Develop methods for metabolic network reconstruction
- Create user-friendly data analysis tools:
- Develop user-friendly tools to explore high-dimensional molecular datasets and to share analysis results and insights with other Lesaffre teams.
- Contribute to Lesaffre Projects:
- Participate in the design and execution of research projects.
- Develop close collaborations within cross-functional teams to define appropriate design of experiments and meaningful data analysis strategies.
- Interpret the results of your analyses to gain insights into our microbial strains and/or fermentation processes.
- Communicate research findings insights and recommendations to stakeholders.
- Ensure Operational Excellence:
- Deliver timely results to meet project deadlines.
- Provide high-quality reporting on project contributions.
- Develop robust and documented software components to ensure traceability and reproducibility of your analyses.
- Valorize the outcome of your work through publications and patents.
This role requires a combination of advanced data analysis and computational biology skills a collaborative mindset and a focus on operational excellence to drive impactful outcomes for Lesaffre.
Qualifications :
For this position we require:
- A Master or a PhD degree with 3 years of experience in the field of computational / system biology bioinformatics or a related field.
- Strong experience in analyzing omics data.
- In depth knowledge of microbial biology and cell metabolism in particular of yeast
- Experience in statistical modeling high-dimensional statistics and data visualization.
- Experience with metabolic network modeling (genome-scale metabolic modeling)
- Good programming and development skills (R Python Unix / bash Git AWS DevOps).
- Ability to work collaboratively in a multidisciplinary team environment.
- 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.
- Multi-omics data integration.
- Machine / deep-Learning.
Additional Information :
What can Lesaffre offer you:
- We are a successful family-owned company with long-standing history where people truly matter.
- We promote a sense of fulfilment with a genuine mission: nourish and protect the planet.
- You will experience intellectual challenges within a multi-expertise network.
At Lesaffre diversity is a strength that enriches our culture and our teams. We are committed to offering you a work environment where you can thrive regardless of your background gender age or abilities. We encourage all applications as we believe that diverse perspectives strengthen our ability to innovate and meet the challenges of tomorrow.
Remote Work :
Yes
Employment Type :
Full-time