Computational Protein Design Expert

We are seeking experienced Computational Protein Design experts to explore and evaluate advanced generative AI approaches for protein engineering as part of a frontier AI scientific evaluation initiative. In this role, you will develop challenging scientific evaluation tasks involving de novo protein generation, diffusion-based structure design, protein binder development, and sequence–structure optimization. You will independently conduct computational experiments, evaluate AI-generated protein designs, and develop reproducible benchmarks and technical proof-of-concept results to assess the capabilities and limitations of generative AI models in protein engineering.

Design scientifically rigorous evaluation tasks involving de novo protein design, target-conditioned binder generation, motif scaffolding, and sequence–structure optimization. Develop and execute computational protein design workflows using generative AI models, diffusion-based approaches, and established protein engineering tools. Define task inputs, biological constraints, expected outputs, evaluation criteria, and reproducible experimental protocols. Evaluate AI-generated protein sequences and structures for folding confidence, structural stability predictions, geometric validity, interface quality, novelty, and biological plausibility.

Analyze protein folding, sequence–structure relationships, and protein–protein interactions to assess the quality and feasibility of generated designs. Develop objective scoring rubrics, reference analyses, and computational validation methods to evaluate model performance. Identify model limitations, failure cases, unrealistic structural predictions, and potential weaknesses in generated protein designs. Distinguish computational predictions from experimentally validated results and document scientific assumptions and limitations.

• Python Ph.D. (ongoing or completed) in Computational Biology, Structural Biology, Bioinformatics, Biochemistry, Protein Engineering, or a closely related discipline.
• Hands-on experience in at least one major area: computational protein design, protein structure prediction, molecular modeling, or protein engineering.
• Strong understanding of protein folding, protein structure–function relationships, molecular interactions, and sequence–structure optimization.
• Practical familiarity with computational protein design and structural analysis tools such as RF diffusion, ProteinMPNN, Alpha Fold, Rosetta, PyMOL, or Chimera
  
  X.
• Strong programming skills in Python, with experience developing or executing computational biology workflows.
• Experience working with protein sequence and structural data formats such as FASTA, PDB, and mmCIF.
• Ability to evaluate protein structures, interpret computational predictions, and assess the scientific validity of generated designs.