Postdoctoral Fellow in Computational Medicine
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Postdoctoral Fellow in Computational Medicine (M/W) – Location: GIF‑SUR‑YVETTE, FR – Contract: Post‑doc – Job ID: 10977
Overview
We are seeking a postdoctoral fellow to join our translational medicine research team, focusing on deciphering and modeling therapy resistance in Acute Myeloid Leukemia patients by applying pioneering AI‑based approaches at the intersection of multi‑omics characterization and disease understanding.
Benefits
- Impactful research investigating intra‑tumoral heterogeneity and therapy resistance.
- Innovative environment: lead efforts in benchmarking AI‑driven methods for scRNA‑seq analyses, annotating cell clusters, identifying malignant populations, and reconstructing clonal phylogenies.
- Collaborative team bridging data science and clinical application, with frequent interactions with R&D and IT.
Responsibilities
- Self‑document on state‑of‑the‑art methods of interest for the project.
- Implement, benchmark, and share appropriate methodologies in R or Python for the purpose of the project.
- Perform comprehensive multi‑omic data analysis to characterize and model relapse‑specific tumor clones.
- Identify biomarkers or predictive signatures associated with therapy resistance.
- Synthesize and interpret analyses in written reports in English.
- Share selected project outcomes through scientific publications in peer‑reviewed journals, posters, and/or oral presentations at conferences.
- Collaborate with cross‑functional teams (R&D, IT) to ensure integration of research efforts.
Qualifications
- PhD in Bioinformatics, Biostatistics, or Data Science, with demonstrated expertise in single‑cell omics data analysis.
- Hands‑on experience with single‑cell sequencing technologies (e.g., scRNA‑seq, proteogenomic) and comfort working with complex, high‑dimensional datasets.
- Proven experience in developing data science (Machine Learning, AI) applications for translational research projects.
- Excellent skills in R and/or Python, including code sharing and versioning.
- Proficiency with Linux environments, HPC, and cloud computing.
- Good knowledge of molecular biology and proven experience in single‑cell data analysis for oncology.
- Scientific level English (written and spoken).
- Ability to work closely with multidisciplinary teams with good organization and communication skills.
EEO Statement
We are committed to equal opportunities and developing talents in all their diversity. We value both experience and the desire to engage daily in contributing to therapeutic progress for the benefit of patients.
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