Post Doc for Protein De Novo Design / all genders
Core
Develop and integrate deep learning models for de novo protein design to create novel therapeutic variants and explore alternative protein scaffolds.
Role type
Post-doctoral researcher (computational protein design)
Builds
Novel protein variants and AI-based design workflows for therapeutically relevant targets
Domain
Biopharma / Computational Biology / AI for Drug Discovery
Deliverable
production ML models
Required skills
de novo protein design, generative protein language models, diffusion and flow matching approaches, Python, Rosetta, proteinMPNN, RFdiffusion, large biological data set management, automated data pipelines, cloud and HPC environments
Preferred skills
antibody/NANOBODY structure and engineering, physical principles of protein folding and complex formation, cross-functional collaboration
Technologies
Python, RFdiffusion, proteinMPNN, Rosetta, pyRosetta
Responsibilities
Explore alternative protein scaffolds as potential therapeutics; Contribute to the evolution of the computational platform for Antibody/NANOBODY de novo design; Drive the development, training, and integration of novel deep and machine learning-based models for protein design & optimization; Collaborate with interdisciplinary screening and engineering teams to define strategies for experimental validation; Apply computational workflows to design novel variants in the context of therapeutically relevant targets
Seniority
Post-doctoral Fellow, hands-on IC