Computational Protein Design Expert

Remote • Contract • via Turing

About this role

About Turing

Turing is one of the world’s leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent.

Role Overview:

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.

What you'll do:

• 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.

• Prepare reproducible evaluation benchmarks, computational analysis reports, and technical documentation.

• Summarize findings in concise technical reports and contribute to proof-of-concept demonstrations for scientific AI evaluation initiatives.

What we're looking for:

• 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 RFdiffusion, ProteinMPNN, AlphaFold, Rosetta, PyMOL, or ChimeraX.

• 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.

• Strong analytical and problem-solving skills with the ability to independently design experiments, evaluate results, and identify technical limitations.

• Excellent written communication skills for documenting scientific findings, evaluation methodologies, and technical reports.

Nice to have:

• Experience with generative AI or diffusion-based protein design models, particularly RFdiffusion or similar approaches.

• Hands-on experience in de novo protein design, protein binder design, motif scaffolding, or enzyme engineering.

• Experience with protein sequence optimization, structural refinement, protein, protein docking, or computational affinity assessment.

• Familiarity with computational screening, protein design benchmarking, and automated evaluation pipelines.

• Experience developing scientific evaluation tasks, scoring rubrics, reference solutions, or reproducible computational benchmarks.

• Experience evaluating AI-generated biological structures, scientific foundation models, or generative protein design systems.

• Research experience involving computational protein engineering, molecular simulations, or structural bioinformatics.

• Publications, research contributions, or open-source development experience in computational biology or protein design.

• Prior experience in AI training, scientific model evaluation, technical proof-of-concept development, or research collaborations.

Expected Deliverables:

• A curated collection of reproducible computational protein design evaluation tasks, including clearly defined inputs, expected outputs, and objective scoring rubrics.

• Computational analysis of AI-generated protein designs, documenting structural quality, biological plausibility, model limitations, and failure cases.

• A concise technical report summarizing evaluation findings, supported by a proof-of-concept demonstration for a potential scientific AI evaluation partnership.

Offer Details:

• Commitments Required: At least 4 hours per day and 40 hours per week with overlap of 4 hours with PST. 

• Employment type  : Contractor assignment (no medical/paid leave)

• Duration of contract : 1 month; [expected start date is next week]

• Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico

Key skills

• PhD Biology
• Bioinformatician / Computational Biologist

Details

• Pay: Shared during the application process
• Company: Turing
• Location: Remote
• Eligible locations: India, Pakistan, Nigeria, Kenya, Egypt, Ghana and 3 more
• Platform: Turing