↳Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field.
↳Strong experience in one or more of the following areas: generative AI, biomedical foundation models, geometric deep learning, multi-modal learning, and large-scale knowledge graphs.
↳Excellent programming skills and proficiency in deep learning frameworks such as PyTorch, with openness to learning new tools and technologies.
↳Practical experience across ML and LLM software stack, including feature engineering, model development, deployment, and validation.
↳Prior experience working with omics data and familiarity with oncology drug development.
↳Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams.
↳Demonstrated strong research skills, evidenced by publications in top-tier ML/AI conferences and/or leading scientific journals.
