Senior Computational Biologist - Multi-omics for Target Discovery and Validation

Senior Computational Biologist - Multi-omics for Target Discovery and Validation

Pierre Fabre

Haute-Garonne or Hauts-de-Seine, France

Your mission

We are seeking a talented and highly motivated Senior Computational Biologist - Multi-omics for Target Discovery and Validation with strong expertise in multi-omics analysis applied to target discovery and validation. You will work at the interface between the Data Science & Biometry and the Drug Discovery Departments, collaborating daily with biologists to drive the discovery and validation of therapeutic targets.

You will be a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care. You will be responsible for exploring, mining and integrating proprietary and public high-dimensional biological data (genomics, transcriptomics, proteomics, functional screens) to test and validate cancer vulnerabilities across indications.

The role sits within the Target & Drug Discovery Data Science team. You will contribute to and be responsible for discovery portfolio projects, and you collaborate on them together with the other Data Science teams, including the Computational Chemistry, Biomarker Development and the Methods & Innovation team.

Your role within a pioneering company in full expansion:

Key Responsibilities

• Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications and immuno-dermatology.
• Process, analyze, and interpret molecular datasets from clinical studies, including genomics, bulk and single-cell transcriptomics, spatial transcriptomics, proteomics, and epigenomics.
• Apply machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
• Contribute to and be responsible for discovery portfolio projects, aligning priorities and activities with the drug discovery collaborators.
• Contribute to the team target ID and validation strategies, and stay up-to-date with the relevant literature and data landscape.
• Work with HPC and/or cloud environments to scale up large data mining and analyses campaigns.
• Work according to industry standards good-coding practices and reproducible research.
• Thrive in a collaborative, inclusive team culture built on trust, creativity, openness, and scientific curiosity where your ideas are valued and your voice matters.

Who you are?

Your skills at the service of innovative projects:

Key Qualifications

• PhD or Master’s degree in Bioinformatics, Computational Biology, Data Science, or a related field.
• 5+ years of experience in computational biology applied to target discovery and validation.
• Solid understanding of cancer biology and the molecular mechanism of cancer vulnerabilities.
• Demonstrated experience in multi‑omics data analysis for target discovery and validation.
• Strong proficiency in R and Python.
• Familiarity with HPC and/or cloud computing environments.
• Familiarity with FAIR data principles and reproducible research.
• Demonstrated ability to thrive in cross functional, matrixed project teams, contributing effectively to multidisciplinary research.
• Strong communication, organizational, and interpersonal skills, including the ability to collaborate, present results clearly, and engage with diverse scientific partners.
• Genuine passion for applying computational biology for improving human health through drug discovery.
• Professional proficiency in English (written and oral).

Preferred Qualifications

• Experience in applying machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
• Familiarity with nextflow (nf-core) pipelines for multi-omics data preprocessing.
• Familiarity with TileDB data infrastructure.
• Familiarity with applying agentic-AI workflows to computational biology.
• Strong publication record or external visibility in scientific communities.