Intern, Protein Design

Adaptyv seeks an Intern for Protein Design to work on automated lab experiments, benchmark AI methods, and build computational tools for protein design.

The company is developing an automated laboratory where AI agents conduct biological experiments. This role focuses on applying and improving protein design methods within this infrastructure, contributing to both internal research campaigns and open scientific initiatives.

Responsibilities

• Evaluate open-source protein design algorithms using actual company targets and wet lab experimental results.
• Create binders for internal research projects and monitor their performance through metrics like hit rates, kinetics, and developability.
• Develop computational tools for structure prediction, filtering, and ranking to narrow down large design sets for synthesis.
• Assist with open competitions and hackathons by writing track descriptions, helping participants, judging entries, and documenting outcomes.
• Share open data, write blog posts, highlight designers, and compare methods on the Proteinbase platform.

Requirements

• Currently pursuing a Master's, PhD, or final-year undergraduate degree in computational biology, machine learning, biochemistry, biophysics, bioengineering, or a closely related discipline.
• Practical experience using at least one modern open-source protein design method.
• Proficiency in Python and PyTorch, with comfort handling biology data formats.
• Solid understanding of binding kinetics and developability, maintaining a critical view of computational scores as definitive truth.

Nice to have

• Previous open-source contributions to a protein design repository, strong performance in a public design competition, or a published blog post or paper.

What the company offers

• An internship duration of 3 to 6 months.

About the company

Adaptyv is one of the fastest-growing biotech firms, trusted by leading biopharmas, frontier AI labs, and techbio companies. The company is building infrastructure that gives AI agents access to the physical world, entering an era of agentic science where AI models design novel proteins, propose hypotheses, and iterate on experimental results.

• Opportunity to advance important work in biotech during the era of agentic science.
• Work with a deep software and hardware stack including API-controllable hardware, orchestrated devices, full observability, processing pipelines, and AI systems.

How to apply

Documents to submit:

• GitHub repository
• Competition submission
• Blog post