Data Scientist en Génomique et Cancer — Stage 6 mois (Remote)

Pierre Fabre Laboratories; Toulouse; Hybrid; EUR 11,000 - 20,000; Full time

Benefits offered by this job

Restaurant on site

Meal vouchers

Remote one day per week after month 1

Job summary

Pierre Fabre Laboratories offers an internship at the Langlade site in Toulouse, France, for 6 months starting January 2027. You will design and develop an internal oncogenicity classification tool, including an API for the Data Science team and a front-end interface for R&D users.

Responsibilities include data curation from public sources, ML model development, and documentation transfer. Benefits include diverse assignments, attractive stipend, one remote work day per week after onboarding,

Qualifications

• Proficiency in Python or R (strong expertise in one language required).
• Solid knowledge of cancer genomics and somatic variant interpretation.
• Interest in machine learning applied to biology (e.g., XGBoost, Random Forest).
• Ability to develop a simple web application to make results accessible to non-technical users.

Responsibilities

• Data collection and preparation of training datasets from public sources (COSMIC, cBioPortal/TCGA/ICGC, ClinVar).
• Develop and implement the variant annotation pipeline.
• Design and develop the oncogenicity classification model and validate its performance.
• Deploy the model via an internal API and develop a front-end application for R&D users.
• Prepare documentation and ensure smooth knowledge transfer.

Skills

Python or R

Cancer genomics

Somatic variant interpretation

Machine learning in biology

Web app development

Documentation

Education

Master's degree in bioinformatics / computational biology

Job description

Pierre Fabre Laboratories offers an internship at the Langlade site in Toulouse, France, for 6 months starting January 2027. You will design and develop an internal oncogenicity classification tool, including an API for the Data Science team and a front-end interface for R&D users.

Responsibilities include data curation from public sources, ML model development, and documentation transfer. Benefits include diverse assignments, attractive stipend, one remote work day per week after onboarding,