Postdoctoral Fellow in Computational Medicine (M/W)

Servier Group; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

Servier Group is seeking a postdoctoral fellow in France to advance cancer treatment through innovative data science methodologies. This role involves researching intra-tumoral heterogeneity in leukemia, utilizing AI and multi-OMIC techniques.

Key responsibilities include implementing data analysis methods, identifying biomarkers, and collaborating with multidisciplinary teams. The ideal candidate will hold a PhD in Bioinformatics or related fields, with robust experience in single-cell data analysis and programming in R/Python.

Qualifications

• PhD in Bioinformatics, Biostatistics, or Data Science, with expertise in single-cell omics data analysis.
• Hands-on experience with single-cell sequencing technologies, ideally scRNA-seq.
• Proven experience in developing data science applications for translational research.
• Excellent skills in R and/or Python, with versioning experience.
• Proficiency with Linux environments and cloud computing.

Responsabilités

• Self-document on state-of-the-art methods relevant to the project.
• Implement and benchmark methodologies in R or Python.
• Analyze multi-omic data to characterize tumor clones.
• Identify biomarkers linked to therapy resistance.
• Report analyses in written format in scientific English.
• Share findings through publications, posters, and presentations.
• Collaborate with R&D and IT teams to ensure research alignment.

Connaissances

Bioinformatics

Data Science

Machine Learning

R Programming

Python

Linux

Single-cell omics data analysis

Formation

PhD in Bioinformatics, Biostatistics, or Data Science

Outils

scRNA-seq

High-dimensional datasets

Description du poste

Are you a dynamic and innovative researcher passionate about advancing cancer treatment through data science? We are seeking a postdoctoral fellow to join our translational medicine research team, focusing on deciphering and modeling therapy resistance. This is a unique opportunity to play a crucial role in understanding intra‑tumoral heterogeneity in Acute Myeloid Leukemia patients by applying pioneering AI‑based approaches at the intersection of multi‑OMIC characterization and disease understanding.

Why Join Us?

• Impactful Research: Investigating intra‑tumoral heterogeneity is critical to uncovering why treatments fail in AML. By integrating multi‑omics data with and without temporal components, you will uncover the molecular and cellular mechanisms underlying disease progression and treatment resistance.
• Innovative Environment: Lead efforts in benchmarking and applying AI‑driven methods to scRNA‑seq analyses. You will have the chance to annotate cell clusters, identify malignant populations, and reconstruct clonal phylogenies to understand evolutionary dynamics across patient response status.
• Collaborative Team: Work in an environment that bridges the gap between data science and clinical application, featuring frequent interactions with internal R&D and IT teams to ensure research alignment with broader organizational goals.

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.

Profile

• 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.

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.