We are sharing a specialised part-time research opportunity for molecular biology experts with advanced expertise in nucleic acid sequence design, synthetic biology, genetics, or related life science disciplines to contribute to the development and evaluation of advanced AI models.
Selected professionals will work on technically demanding molecular biology problems involving DNA and RNA sequence design, model evaluation, and expert-quality training data. The work focuses on identifying weaknesses in AI reasoning, developing rigorous biological tasks and reference solutions, and establishing standards for high-quality molecular biology outputs.
Key Responsibilities
Molecular Biology Task Design & Sequence Engineering
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Design technically challenging molecular biology tasks grounded in real-world experimental and sequence-design workflows
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Develop accurate, well-documented expert solutions that can serve as reference-quality ground truth
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Work across sequence types including PCR, qPCR and cloning primers, plasmids and expression vectors, gRNA and sgRNA constructs, mRNA and RNA constructs, and HDR or repair templates
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Apply appropriate cloning strategies such as Gibson assembly, Golden Gate, Gateway, restriction-based cloning, and related approaches
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Incorporate considerations such as codon optimisation, regulatory elements, sequence specificity, and experimental feasibility
AI Model Evaluation & Biological Reasoning
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Review model-generated molecular biology outputs and identify where biological reasoning or sequence-design logic breaks down
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Compare AI responses against expert-quality reference solutions for correctness, rigour, and biological validity
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Identify incorrect assumptions, missing constraints, or technically weak reasoning within generated outputs
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Provide clear written explanations of why a proposed biological design is correct, incomplete, or unsuitable
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Help improve model performance on complex molecular biology and sequence-engineering problems
Quality Standards, Guidelines & Rubrics
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Develop guidelines and evaluation rubrics for assessing the quality of molecular biology sequence designs
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Define appropriate standards for guide and target selection, homology arm length, primer melting temperature, specificity, codon optimisation, and regulatory elements
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Establish clear criteria for evaluating experimental plausibility and biological accuracy
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Translate specialist molecular biology knowledge into structured standards that can be applied consistently across research workflows
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Support consistency and quality across datasets produced by multiple subject-matter experts
Scientific Research & Expert Collaboration
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Collaborate with research, engineering, and other domain experts working on advanced AI development
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Apply deep subject-matter expertise to improve the quality and reliability of scientific training data
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Explain complex molecular biology design choices clearly and precisely in written form
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Contribute insights grounded in experimental research, peer-reviewed scientific work, and practical sequence-design experience
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Maintain clear boundaries around confidential, unpublished, proprietary, or institution-owned information
Ideal Profile
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Advanced degree in molecular biology, genetics, biochemistry, synthetic biology, bioengineering, or a closely related life science discipline, with a PhD strongly preferred
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Substantial hands-on experience designing nucleic acid constructs before experimental execution
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Practical expertise across several areas including primers, plasmids and vectors, gRNA and sgRNA, mRNA constructs, and HDR or repair templates
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Strong understanding of cloning strategies including Gibson assembly, Golden Gate, Gateway, restriction-based approaches, and codon optimisation
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Strong peer-reviewed publication record, with first-author research in recognised scientific journals highly valued
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Clear record of scientific and professional progression
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Ability to explain complex experimental and sequence-design reasoning clearly and precisely
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Strong written communication and analytical skills
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Previous experience in AI training, model evaluation, scientific annotation, or structured data-review workflows is advantageous
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Based in the United States
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Ability to commit reliably to at least 20 hours per week on weekdays
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Publication links should be provided where available
Engagement Details
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Part-time employment-based engagement
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Fully remote within the United States
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Minimum availability of 20 hours per week on weekdays
- Compensation: $60–$95/hour
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Work will involve advanced molecular biology task development, AI evaluation, and scientific quality review
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Selected professionals may contribute as part of an extended research workforce supporting advanced AI development
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Project scope, duration, workload, and responsibilities may evolve depending on research requirements
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Work must be completed without using confidential or proprietary information belonging to any employer, client, laboratory, institution, or other third party
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H1-B and STEM OPT support is unavailable for this engagement
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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