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.

• 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.