POD Lead - Computational Protein Design Expert

Zettamine Labs; United States; Remote; USD 730 - 1,300; Full time

Job summary

ZettaMine is seeking a Freelance POD Lead Computational Protein Design Expert for a short-term Frontier AI Research initiative in protein engineering and generative AI evaluation. This remote role from India requires a PhD and hands-on design experience, with a focus on rigorous evaluation and reproducible analyses.

The position entails developing workflows, assessing AI-generated protein structures, and delivering technical reports within a three-week window.

Qualifications

• PhD in Biology/Biochemistry or related field.
• Hands-on experience with computational protein design and protein engineering tools.
• Strong programming in Python and workflows for computational biology.

Responsibilities

• Design challenging evaluation tasks for de novo protein generation and binder design.
• Develop and execute computational protein design workflows using generative AI models.
• Evaluate AI-generated protein sequences for folding confidence and biological plausibility.
• Develop objective scoring rubrics and reproducible benchmarks.
• Document evaluation findings and limitations in technical reports.

Skills

Python workflows

Protein design evaluation

Written communication

Education

PhD in Biology/Biochemistry or related

Tools

RFdiffusion

ProteinMPNN

AlphaFold

Rosetta

PyMOL

ChimeraX

Job description

Hello,

Greetings from ZettaMine!!!

Freelancing Opportunity:

We are hiring a POD Lead Computational Protein Design Expert for a short-term Frontier AI Research, Protein Engineering & Generative AI Evaluation initiative..

Location:

India

Role:

POD Lead Computational Protein Design Expert

Educational Eligibility:

PhD ( Biology / Biochemistry or Related )

Mode:

Remote-Freelancing

Duration:

3 Weeks

Mandatory Eligibility Criteria

Technical Qualification

• Hands-on experience in 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 experience with tools such as RFdiffusion, ProteinMPNN, AlphaFold, Rosetta, PyMOL, or ChimeraX.
• Strong programming skills in Python and experience developing or executing computational biology workflows.
• Experience working with protein sequence and structure formats, including FASTA, PDB, and mmCIF.
• Ability to evaluate protein structures for structural quality, stability predictions, interface quality, novelty, and biological plausibility.
• Experience designing computational experiments, evaluating scientific results, and identifying model limitations.
• Strong analytical skills and excellent written communication for scientific documentation and technical reporting.

Preferred Qualifications

• Experience with generative AI and diffusion-based protein design models.
• Hands-on experience in de novo protein design, protein binder design, motif scaffolding, or enzyme engineering.
• Familiarity with protein-protein docking, structural refinement, and computational affinity assessment.
• Experience developing scientific benchmarks, scoring rubrics, and automated evaluation pipelines.
• Research publications or open-source contributions in computational biology, structural bioinformatics, or protein engineering.
• Previous experience in AI model evaluation, scientific proof-of-concept development, or research collaborations.

What You'll Work On

• Design challenging scientific evaluation tasks involving de novo protein generation, binder design, motif scaffolding, and sequence-structure optimization.
• Develop and execute computational protein design workflows using generative AI models and established protein engineering tools.
• Evaluate AI-generated protein sequences and structures for folding confidence, geometric validity, interface quality, and biological plausibility.
• Develop objective scoring rubrics, reference analyses, and reproducible computational benchmarks.
• Identify model limitations, failure cases, and unrealistic structural predictions.
• Prepare technical reports documenting evaluation findings, scientific assumptions, and limitations.
• Deliver a curated collection of reproducible evaluation tasks and a computational proof-of-concept demonstration.

Availability Requirements

• Minimum 40 hours per week.
• At least 4 hours of availability per day.
• Minimum 4 hours of overlap with PST business hours.

Employment Type

Contractor assignment (no medical or paid leave).

Thanks & Regards,

Karthik K

ZettaMine