Protein and Vector Engineering

About

At WhiteLab Genomics, we believe that every patient deserves access to life-saving treatments. We won’t rest until that belief becomes a reality.

Driven by our commitment to transforming the future of healthcare, we’ve earned our place among the top innovators, including Y Combinator, French Tech 2030, and Future 40 by Station F. We’ve also been recognized by The Galien Foundation as a “Best Startup” in healthcare innovation and as Manufacturing Tech Disruptor of the Year - 2024 at Advanced Therapy Awards: Phacilitate in the USA, among other accolades.

We're committed to revolutionizing genomic medicine, delivering single-dose cures to millions with cancer and neurodegenerative and rare diseases worldwide.
By integrating cutting-edge data science, computational biology, and structural biology to design genomic medicine vectors with unprecedented precision, we're advancing the frontiers of healthcare and addressing critical challenges with the highest stakes.

If you’re passionate about improving patient outcomes and the intersection of biology and technology, we’d love to meet you!

Join us – together, we’ll bring life-saving treatments to the people who need them most.

Job Description

You will be hierarchically managed by the Head of the Protein and Vector Engineering team and also be closely mentored on scientific and technical matters by experienced members of the team. This structure provides mentorship and ensures the rigor and quality of scientific contributions while encouraging the development of technical autonomy over time.

Apply and develop methods in 3D structure prediction, molecular dynamics (MD), free energy calculation, protein engineering, and computational drug design.

  • Use AI/ML approaches to improve Computational Drug Design workflows and accelerate drug discovery projects.

  • Develop and implement computational pipelines and models integrating structural, chemical, and genomic datasets.

  • Collaborate across teams to support discovery and optimization projects.

  • Contribute to internal tool development and benchmarking, leveraging platforms such as Schrödinger, Rosetta, PyMOL, AlphaFold, and other state-of-the-art molecular modelling suites.

  • Communicate results effectively with both technical and non-technical stakeholders.

Preferred Experience

  • Ph.D. in Structural Bioinformatics, Genomics, Computational Chemistry, Data Science or another relevant area – OR – Master’s degree in Structural Bioinformatics, Machine Learning, Computational Biology (or related) with strong applied experience.

  • Solid knowledge of molecular modelling**, structural biology, and computational chemistry**.

  • Demonstrated experience in computational drug design (small molecules and/or biologics).

    Core skills:

  • 3D structure prediction, molecular dynamics,

  • Antibody design, molecular modelling

  • AI/ML applied to drug design and/or molecular modelling

  • Programming: Bash, R or Python, version control (GitHub)

    Tools/Software:

  • Schrödinger, MOE, or any modelling software

  • Rosetta, PyMOL,

  • AlphaFold (and similar packages)

    Nice to have:

  • Experience with cloud/HPC environments for large-scale molecular simulations.

  • Knowledge of best practices in reproducible research and workflow management.

  • Familiarity with drug discovery pipelines from hit identification to lead optimization.

  • Previous experience in dealing with Peptide modelling is a major asset.

  • Relevant experience in relational querying biological databases experience.

Additional Information

  • Contract Type: Full-Time
  • Location: Paris
  • Education Level: PhD and more
  • Experience: > 3 years
  • Possible partial remote
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