Develop cutting edge model interpretability tools to distill knowledge learned by high performing deep neural networks in functional genomics.
Qualifications: A PhD in Computational Biology, Bioinformatics, Computer Science or related field is required. Strong computational biology and machine learning experience is required. Ideal candidates will be self-driven, have strong written and oral communication skills, and a desire to work in an interdisciplinary environment. Experience with causal discovery, graph neural networks, and reinforcement learning is a plus.
Develop machine learning solutions in digital pathology to study cancer dynamics.
Qualifications: A PhD in Computer Science, Applied Math, Machine Learning, Physics, Mathematical/Computational Biology, Enginneering, or related field is required. Strong machine learning experience in computer vision is required. Ideal candidates will be self-driven, have strong written and oral communication skills, and a desire to work in an interdisciplinary environment. Experience with latent variable models, diffusion models, and neural ODEs is a plus.
Apply: Interested applicants should submit a cover letter with a brief statement of research interests, CV, and contact information for 2-3 references to koo@cshl.edu.
We have openings for graduate students at CSHL and Stony Brook University. Email koo@cshl.edu to discuss rotatation opportunities.