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Postdoctoral researcher in the Laboratory of Cellular metabolism, located at the Institute of Biotechnology in BIOCEV. We are a young, international research team that studies the metabolic crosstalk in healthy and tumor tissue using genetic mouse models, functional screens, and single cell and spatial omics technologies. The successful candidate will lead a project focused on tumor microenvironment and metabolism, with a particular emphasis on immune–endothelial cell interactions in tumors. Single-cell and spatial transcriptomics will be key tools in this project, together with complementary experimental approaches in vitro and in vivo, to understand metabolic regulation in the tumor microenvironment.
Job Responsibility:
Analyze and interpret high-dimensional datasets from tumor microenvironment samples (including scRNAseq and related omics outputs)
Identify and characterize functional states of immune and endothelial cell populations, including their dynamics and potential interactions
Analyze and quantify multiplex histochemistry data (from Akoya PhenoCycler), including spatial organization and cell–cell neighborhood relationships
Integrate results across datasets and generate clear, publication-quality figures and reports
Present results in lab meetings and contribute actively to scientific discussion and planning
Contribute to manuscript preparation and support fellowship/grant-related writing
Lead a project focused on tumor microenvironment and metabolism, with a particular emphasis on immune–endothelial cell interactions in tumors
Oversee your research project while working as part of a collaborative team at the interface of cancer metabolism, vascular biology, and tumor immunology
Active contribution to scientific discussions, manuscript preparation, and communication of results at international meetings, as well as support in mentoring junior colleagues
Requirements:
PhD in immunology, cancer biology, computational biology, bioinformatics, or a related field
Strong track record shown by publications in peer-reviewed international journals
Hands-on experience with single-cell and/or spatial omics analysis (scRNAseq preferred
additional spatial/imaging-based analysis is a plus)
Practical programming and data analysis skills (R and/or Python)
ability to generate reproducible analyses and clear data visualizations
Ability to work independently, manage priorities, and communicate results effectively
Excellent command of English (written and spoken)
Strong data analysis skills and enjoy working with large, complex datasets (e.g., single-cell, spatial, imaging-based or other omics data)
Practical experience working in R and/or Python for biological data analysis and visualization
Interested in tumor–stroma interactions, particularly immune–endothelial crosstalk
Background in immunology and can confidently interpret immune cell states and activation programs in tumors
Communicate results clearly and work well both independently and in a team
Enjoy working with smart and creative people in a truly international environment