Research Scientist Intern, AI Molecular Design

GenBio AI is building the Virtual Cell World Model - a persistent, multimodal AI system that predicts, simulates, and ultimately programs cellular behavior. Rather than producing isolated predictions, the Virtual Cell enables scientists to query cellular states, perform virtual perturbations, and design new biological interventions within a unified computational world. Together with AIDO Foundry, our AI-native engineering framework for automating Virtual Cell development, we are building the software infrastructure for the next generation of AI-driven drug discovery.

Qualifications:

- 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 6-month, in-person internship in Palo Alto, CA, and authorized to work in the U.S. for the duration of the internship.

- 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.

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

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

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

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

Nice to Have:

- 3 year PhD student and above.

- 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.

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

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

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

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

- Experience in large-scale distributed training and inference.

- 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.