R&D Where your curiosity drives the miracles of science

Frankfurt am Main

Ready to grow your skills while helping shape the future of healthcare? At Sanofi, you’ll be empowered to learn, ask questions, and bring your ideas to life – all while supported by inspiring mentors and collaborative teams

About Sanofi

Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions.

About us

The Virtual Screening and Property Prediction group is part of the Digital Biologics Platform (DBxP) in Sanofi R&D. We develop and apply physics-based modeling, molecular simulation and machine learning workflows to support the discovery and optimization of therapeutic proteins (antibodies and nanobodies®). Be part of our team Computational Biophysics for Protein Property Prediction as an intern .

Job Description

Predicting protein properties such as stability and aggregation is an important part of developing protein therapeutics. Proteins are flexible molecules, and their conformational dynamics can affect how they behave in experiments. In this internship, you will investigate whether information from molecular simulations can help predict these properties, using in-house experimental data.

Your tasks :

  • Set up, run and analyze Molecular Dynamics and Monte Carlo simulations of proteins, mainly antibodies and nanobodies.
  • Calculate descriptors from the simulations (e.g. flexibility, conformational ensemble characterization, surface properties) and relate them to experimental data.
  • Build a predictive workflow that combines simulation-derived descriptors with statistical or machine learning models.
  • Benchmark publicly available prediction tools, including generative AI for structural ensemble prediction, against Sanofi in-house data.
  • Present your results to computational and experimental colleagues and document the workflow.

Requirements & Qualifications

  • You are currently enrolled in full-time in a master’s program in biophysics, computational chemistry, structural biology, bioinformatics, physics or a related field
  • Mandatory internship of 6 months
  • Experience with Molecular Dynamics and/or Monte Carlo simulations and classical molecular modeling (e.g. GROMACS, AMBER, OpenMM, Rosetta, Maestro, MOE, pymol, etc.)
  • Programming skills in Python and experience working in Linux environments.
  • Knowledge of protein structure, in particular antibodies or nanobodies, is a plus.
  • Experience with AI or machine learning (e.g. scikit-learn, PyTorch, protein language models, structure prediction tools) is a plus.
  • Curiosity, independence, structured way of working, good communication skills and enjoyment of teamwork.
  • Fluent English, written and spoken

Why Choose Us

  • Bring the miracles of science to life alongside a supportive, future-focused team
  • An international work environment , in which you can develop your talent and realize ideas and innovations within a competent team
  • Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally
  • Benefit from our mobile office policy working up to 60% hybrid, depending on the area of assignment, within Germany
  • Play an instrumental part in creating best practice
  • Start your career at our Frankfurt site and experience our modern working environment

Pursue Progress . Discover Extraordinary .

Join Sanofi and step into a new era of science - where your growth can be just as transformative as the work we do. We invest in you to reach further, think faster, and do what’s never-been-done-before. You’ll help push boundaries, challenge convention, and build smarter solutions that reach the communities we serve. Ready to chase the miracles of science and improve people’s lives? Let’s Pursue Progress and Discover Extraordinary – together.

At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, protected veteran status or other characteristics protected by law.

Veröffentlicht am 2026-11-12

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