Research Scientist Intern, AI Molecular Design (Winter/Spring)

GenBio AI
Location
Palo Alto, CA
Job Type
Full-time
Posted
October 31, 2026
Salary Range
$8k - $10k USD

Job Description

GenBio AI is an AI for Science company on a mission to make biology fully computable. We are building AIDO (AI-Driven Digital Organism) to simulate living systems, decode biology holistically, and accelerate medical and scientific research. Our first step toward that mission is AIDO Cell, the first virtual cell world model that holistically simulates cell biology from molecules up to whole-cell behavior. It enables researchers to run experiments virtually, predicting how cells respond to genetic changes, drugs and other interventions before going into the lab. It is supported by AIDO Foundry, an AI-builds-AI engineering framework for automating virtual cell development, and AIDO Lab, an interface to digitally run experiments and observe the results. Together they form the foundation for a new paradigm in AI-driven drug discovery, bioengineering, and fundamental biomedical research.

Qualifications

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M.S. or Ph.D. student (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.

  • Available for a 3-month, in-person internship in Palo Alto, CA, and authorized to work in the U.S. for the duration of the internship. Internship is expected to start January 2027.

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Skilled in developing, implementing, and debugging deep learning methods/models in popular frameworks, such as JAX, TensorFlow, or PyTorch, with an interest in generative models, graph neural networks, or large-scale deep learning applications.

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Strong theoretical foundation (e.g., statistics, optimization, graph theory, linear algebra).

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Passion for interdisciplinary research (emphasizing the intersection of AI and Biology), and willingness to acquire necessary domain knowledge.

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Motivated and self-driven with the ability to operate with partial descriptions of high-level objectives (as is typical in a start-up environment).

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Familiarity with software engineering best practices (version control, documentation, etc).

Nice to Have

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3 year PhD student and above.

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Proven track record in research and innovation demonstrated through contributions in top-tier AI/ML (e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICLR) and/or core biology (e.g., Nature, Science, or Cell) journals and conferences.

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Intern experience in industry (e.g., OpenAI, FAIR, Deepmind, Google Research).

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Hands-on experience working at the intersection of AI and Biology, particularly protein structure prediction, protein sequence/structure modeling, or molecular design.

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Experience with biological structure prediction algorithms or models such as AlphaFold2/3 or RoseTTAFold.

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Experience in generative modeling for biological structures and sequences, including diffusion models, flow matching, or related approaches.

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Experience in large-scale distributed training and inference.

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Open-source contributions, especially if used by others.

Join us as we embark on this journey to redefine the future of biology and medicine.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security’s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov.

Frequently Asked Questions

Where is this internship located, and what is the work policy?
The job is located in Palo Alto, CA. It is a 3-month, in-person internship starting around January 2027.
What qualifications and experience are required for this role?
Candidates should be M.S. or Ph.D. students (or equivalent) in CS, AI, ML, or a related field. Requirements include JAX, TensorFlow, or PyTorch skills, a strong theoretical foundation, software engineering best practices, self-motivation, and U.S. work authorization for the internship duration.
What background or experience is nice to have?
Preferred qualifications include being a 3rd-year+ Ph.D. student, top-tier research publications (e.g., NeurIPS, Nature), prior industry research interning, experience with biological AI/models (like AlphaFold or diffusion models), large-scale distributed training, and open-source contributions.

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
genbio ai machine learning deep learning artificial intelligence drug discovery protein

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