Computational Protein Design Expert
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
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