Research Scientist Intern at GenBio AI in Palo Alto, CA

Summary: GenBio AI is a newly established start-up headquartered in Silicon Valley, focused on transforming biology and medicine through generative AI. The Research Scientist Intern will conduct AI and computational biology research, improve models, design experiments, and collaborate with AI/ML researchers to develop advanced AI for biology foundation models. Responsibilities: - You will work with the team to conduct cutting-edge AI and computational biology research - Your primary tasks will include improving existing models and exploring new methodologies to advance our AI capabilities in biology - You will work with the team on designing and executing experiments, analyzing complex datasets, and applying statistical techniques to validate the performance and robustness of AI systems - Additionally, you will collaborate closely with the AI/ML researchers and computational biologists on the team to develop our state-of-the-art AI for biology foundation models Required 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 - 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) Preferred Qualifications: - 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 - Experience in large-scale distributed training and inference - Open-source contributions, especially if used by others Required Skills: Deep Learning Important Skills: JAX, TensorFlow, PyTorch, Statistics, Optimization, Graph Theory, Linear Algebra Nice-to-Have Skills: Interdisciplinary Research, Software Engineering Practices, Self-driven