[Hiring] Computational Biologist @Owkin

Role Description

As a Computational Biologist at Owkin, you will have a unique opportunity to contribute to the discovery of better treatments through the development and use of agentic AI systems. An integral member of the Biomedical team, you will work alongside world-class experts in AI and biology within a multidisciplinary team dedicated to pioneering discoveries, all while embedded in an organization that develops end-to-end AI systems for clients. Your experience in omics will allow you to contribute to the building of our AI Scientist, an agentic system designed to navigate the complexities of target and drug discovery.

• Contribute analyses to projects aiming to discover novel drug targets, biomarkers and disease subtypes through reverse translation based on multi-omics patient or pre-clinical data including: genomic, transcriptomic (spatial, single-cell, bulk), proteomic, and others.
• Analyze biomedical datasets using classical or novel omics methods and machine / deep learning algorithms.
• Conduct literature reviews to stay up-to-date with respect to relevant approaches and datasets.
• Participate in the interpretation of results and help design validation strategies together with cross-functional teams.
• Collaborate with other members of Owkin’s R&Tech and Biomedical departments with varied backgrounds (computational biologists and chemists, AI scientists, medical imaging experts, medical doctors, biologists, …).
• Contribute analyses and visualisations to generate scientific internal and external communications and reports.
• Participate in Owkin’s internal R&D activities, develop new as well as improve existing methodologies, strive to keep Owkin’s Toolbox to the state-of-the-art.

Qualifications

• MSc / PhD in either computational biology, bioinformatics, biology, machine learning, computer science, mathematics or a related field.
• Experience working with omics data and NGS data processing pipelines.
• Experience of integrating multi-omics datasets.
• Experience of working in early-stage drug discovery programs, and with tasks such as target identification, biomarker discovery and patient stratification.
• Good knowledge about molecular and cellular biology, especially related to cancer and/or other human diseases, to help interpret analysis results together with our biomedical experts.
• Familiarity with machine learning concepts and toolkits such as: cross validation, statistical tests, scikit learn, xgboost, etc.
• Experience using autonomous AI agents and agentic workflows to perform data analyses.
• Good programming skills in Python.
• Fluency in written and spoken English.

Ways to Stand Out

• Single-cell RNA-seq and spatial transcriptomic data analysis.
• Clinical and biomedical imaging data.
• Hands-on experience with agentic AI systems and their development.
• History of publications or contributions to top-tier academic journals or conferences.
• Have previously worked in a biotech / pharma / life science company.

Benefits

• Flexible work organization.
• Friendly and informal working environment.
• Opportunity to work with an international team with high technical and scientific backgrounds.