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
