Mots-Clés
Transcriptomics
Genomics
Spatial omics
Multimodal studies
Tumor ecosystem
Description
Summary
The research team Computational Cancer Biology, part of the Cancer Data Science unit at Gustave Roussy/IHU-Prism, aims to identify the tumor-intrinsic and tumor-extrinsic determinants of malignant initiation and progression by analyzing high-dimensional data with detailed clinical annotations. Our team focuses on characterizing tumor genomics and intrinsic cellular programs, together with the role of the tissue microenvironment, in disease initiation and progression. We integrate multiple layers of tumor phenotype such as genomics, transcriptomics, and tissue context, with particular attention to how tumor cells interact with the surrounding normal cells of their environment. Using state-of-the-art profiling technologies and machine learning tools, we develop frameworks to study cancer as an evolving ecosystem. Our goal is to decipher the complexity of cancer biology through clinically-relevant study designs, ultimately building tools to predict disease progression and identify new therapeutic vulnerabilities. In this key role, you will apply your bioinformatics, programming and data science skills to generate results from large multiomic patient datasets. You will play a key role in helping to answer the latest questions in cancer research and help facilitate collaborations with diverse research teams to develop comprehensive framework and validate findings in various models.
Project summary
In this role, you will be responsible for processing and integrating the data of our Multimodal Spatially Resolved Pan-cancer Invasion Atlas (STILL project, IHU-Prism) while developing comprehensive frameworks integrating tumor genomics and tissue context. You will work closely with the Interception Program and Clinical Discovery Bioinformatics teams to integrate new samples and additional data modalities. You will apply cutting-edge curated data processing pipelines to generate results from the latest spatial transcriptomic platforms, single-cell technologies, bulk RNA-seq and WES/WGS, and imaging modalities.
Key responsibilities
• Process sample data generated by the Institute and external collaborators.
• Deliver results and provide expertise on QC and results interpretation.
• Ensure the full data processing reproducibility across the team projects.
• Support the metadata management infrastructure.
• Support lab growth through maintaining awareness of developments in the wider bioinformatics and research communities.
• Participate in Gustave Roussy/IHU-Prism meetings, workshops and seminars.
• Contribute to publications when required.
**Key experience and competencies **
The post holder should embody the following values open, dynamic and collegial, in addition to:
Essential Qualifications, experience and competencies:
• A degree in a relevant subject with an extensive analytical component e.g. bioinformatics, statistics, computational biology or mathematics.
• Excellent coding skills in a relevant language e.g. Python, R.
• Excellent Linux and HPC skills.
• Experience of running and developing bioinformatics pipelines using a workflow management system such as Nextflow or Snakemake.
• A good understanding of high-throughput sequencing data processing software and bioinformatics data processing tools.
• An understanding of multi-omics data and data analysis approaches.
• Knowledge of reporting software e.g. quarto, markdown.
• Knowledge of technology ensuring data processing reproducibility e.g. containerisation, environments, change control software.
• Knowledge of the application of statistical techniques to biological data.
• Excellent scientific communication skills within a research environment.
Desirable Qualifications, experience and competencies:
• Familiarity with cancer biology.
• Familiarity with omics data generation protocols.
• Familiarity with visualising omics data analysis results.
• Familiarity with software development processes and management.