Mots-Clés
Immuno-oncologie
Omics data
RNAseq
ExomeSeq
TCRseq
scRNAseq
Spatial transcriptomics
Multiplex imaging
Analyse de données haut débit
Biostatistiques
Programmation R, Python, Java
Description
Expected Responsibilities & Activities of the candidate:
- Use and adapt existing pipelines and develop novel computational methods and tools to analyze complex RNAseq, ExomeSeq, TCRseq, scRNAseq and spatial multiplex datasets.
- Implement computational methods to calculate cell-cell proximity metrics and infer cell neighborhoods from raw data of multiplex-immunofluorescence tumor tissue staining as well as spatial transcriptomics data.
The duties also include:
- Keep abreast of emerging methods in computational biology/bioinformatics, including non-supervised analysis of high-plex immunohistochemistry (IHC).
- Interact with the immunologists of the team to optimize the design of dry experiments and best adapt the analysis pipelines
- Drive the bioinformatics expertise in the team and provide mentorship for students, Engineers and technicians, with possibility to manage a group of 2 to 3 persons according to experience
- Contribute to data synthesis and to the writing of papers
These responsibilities will be adapted to the candidate’ background and experience
Skills and qualifications
- PhD with a solid background in Bioinformatics, Computational Biology or Systems Biology (>2 years of postdoctoral experience would be a plus)
- Experience in utilizing JAVA, Python and R programming languages as well as bioinformatics pipeline development (prior experience in working with high dimensional omics datasets is a real plus)
- Ability to be inventive, to solve problems and present novel ideas in method development and data analysis
- Ability to work independently while being able to communicate effectively and evolve in a multidisciplinary research environment
- Knowledge of tumor immunology will be considered as a plus.
- Broad knowledge of biostatistics (from signal analysis to survival analyses)
- Fluency in written and spoken English.
Example of publications from the lab related to the field
• Locke FL, et al. Nature Med. 2024 Jan 17. (IF: 53.4)
• Scholler N, et al. Nature Med. 2022 Sep;28(9):1872-1882. (IF: 53.4)
• Angelova M, et al. Oncoimmunology. 2021 Apr 25;10(1):1912250. (IF: 7.7
• Galon J, Bruni D. Immunity, 2020 Jan 14, 52 (1), 55-81 (IF: 43.5)
• Mascaux C, et al. Nature. 2019 Jul;571(7766):570-575 (IF: 69.5)
• Galon J & Bruni D. Nature Reviews Drug Discovery. 2019 Mar;18(3):197-218. (IF: 112.3)
• Mlecnik B, et al. Bioinformatics. 2019 Oct 1;35(19):3864-3866. (IF: 6.9)
• Bindea G, et al. Bioinformatics. 2013 Mar 1;29(5):661-3. (IF: 6.9)
• Bindea G, et al. Bioinformatics. 2009 Apr 15;25(8):1091-3. (IF: 6.9)
• Angelova M, et al. Cell. 2018 Oct 18;175(3):751-765 (IF: 66.9)
• Pagès F, et al. Lancet. 2018 May 26;391(10135):2128-2139. (IF: 202.7)
• Van den Eynde M, et al. Cancer Cell 2018 Dec 10;34(6):1012-1026. (IF: 50.3)
• Galon J, et al. Science 2006 313:1960-4 (IF: 63.7)
• Pagès F, et al. N Engl J Med. 2005 Dec 22;353(25):2654-66. (IF: 176.1)