Bioinformatics engineer for single cell data analysis and data integration
Job Title :
Bioinformatics research engineer for single cell data analysis and data integration
General information:
Workplace: IBGC UMR CNRS 5095 - Computational Biology and Bioinformatics team
Expected date of hire: January 2023
Duration of contract: January 2023 - December 2025
Desired level of education: PhD or equivalentExperience required: 1-5 years
Missions
A position of Research Engineer is open for recruitment in the "Computational Biology and Bioinformatics" (IBGC) team to study different omics data mainly in single cell for samples of several pathologies - neurological, inflammatory, autoimmune diseases and cancer. In the team we study different model systems: pain models, tumor samples, PDX (patient-derived xenografts) and cell lines. He/she will handle the pipelines that are already designed in the team, adapt them to future evolutions and generate reports of data analysis results taking into account the requests of the project leaders.
Importantly, he/she will improve the existing pipelines to introduce new methods from the literature search. In addition, several projects concerning the analysis of heterogeneous data are currently underway in the team (single cell or not). Thus, in addition to the single cell data analysis itself, the engineer will also develop data integration methods and apply them to the datasets available in the team.
Activities
The recruited research engineer (2 years) will develop the analysis and data integration pipelines in close collaboration with the biology researchers. He/she will:
- Design innovative and mutualized technological developments, in relation with the projects of the biologist partners
- Lead data analysis and bioinformatics pipelines development projects
- Ensure and organize the scientific and technological watch regarding single cell data analysis and omics data integration
- Disseminate and valorize the results and technological achievements in the form of reports, publications, oral presentations
- Participate in the implementation of a quality approach
Skills
We are looking for a highly motivated individual, passionate about the development of science through technology, with a strong taste for teamwork and excellent communication skills. The successful candidate will have the following skills or experience.
Required skills:
- Proficiency in R and/or Python programming.
- Proficiency in software required for genomic and transcriptomic data analysis (STAR, DeSeq2, CellRanger).
- Proficiency in written and spoken scientific English.
- Practical understanding of genomic and transcriptomic data analysis methods.
- Practical understanding of multivariate data analysis methods (PCA, t-SNE, UMAP, statistical learning, etc.)
- Experience with single-cell data desired but not required (Seurat or Scanpy) as well as spatial data (Seurat, SPATA or SquidPy)
- Experience with other types of omics data would be a plus (e.g. proteomics, metabolomics)
- Working knowledge of containerization tools (Docker, Singularity), version control (Git) and workflow management (Snakemake)
- Strong background in biology; knowledge in cell and molecular biology, immunology or neuroscience would be a plus.
Desired profile:
- Doctoral or engineering degree in bioinformatics, biostatistics or biology
- Experience in bioinformatics applied to genomic or transcriptomic data, ideally at the single-cell level
- Understanding of the main analyses of single-cell sequencing data
- Organizational skills, synthetic presentation of scientific results
- Good communication with researchers in biology, interest in biological issues
- Teamwork skills, ability to listen and make proposals - Autonomy
- Interest in working with others Autonomy - Interest in the methodological aspects of data analysis.
Context of the work
The research engineer will work in the "Computational Biology and Bioinformatics" team (IBGC UMR CNRS 5095, Bordeaux) under the supervision of Macha Nikolski. A strong collaboration is expected with the data generating teams.
How to apply :
