About the role
About Turing:
Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.
Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM, and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.
Role Overview:
Turing is partnering with a leading AI research lab to bring domain experts directly into frontier AI development. We are looking for PhD-level scientists in biology and the life sciences to work alongside the lab’s research teams, applying deep scientific expertise to advance and evaluate cutting-edge AI models. This is a chance to shape how the most advanced AI systems reason about science.
Requirements:
- PhD in Biology or a Life Sciences field (e.g., molecular biology, genetics, biochemistry, cell biology, neuroscience, immunology, microbiology, bioinformatics/computational biology, or related).
- Hands-on research experience, ideally with peer-reviewed publications.
- Ability to create problems that are genuinely difficult, beyond textbook-level knowledge.
- Excellent written English and the ability to explain complex scientific reasoning clearly.
- Strong attention to detail and comfort working independently in a remote setting.
- Strong attention to detail and comfort working independently in a remote setting.
- Design challenging, research-grade scientific problems and tasks that test the limits of frontier AI models and agents.
- Evaluate model and agent outputs for scientific accuracy, rigor, and reasoning quality, and give clear, structured feedback.
- Help build and refine benchmarks and datasets in your area of expertise.
- Identify where models fail on expert-level biology and explain why.
- Collaborate with researchers to translate scientific workflows into tasks AI systems can be trained and tested on.
- Adapt to evolving project scopes as research priorities shift.
- Adapt to evolving project scopes as research priorities shift.
- Experience with Python, R, or command-line tools for scientific computing or data analysis.
- Background in computational biology, bioinformatics pipelines, or lab-to-data workflows.
- Prior experience with AI training, evaluation, data annotation, or benchmark creation.
- Postdoctoral or industry R&D experience.
- Postdoctoral or industry R&D experience.
- Commitments Required: 40 hours per week with 8 hours of overlap with PST.
- Engagement type: Contractor
- Engagement Length: upto 5 weeks
- Engagement Length: upto 5 weeks
- Application and profile review
- AI interview (mandatory)
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