Potential projects include but are not limited to:
(1) Bridge the conceptual divide between flexible deep neural network models and prior biological knowledge of gene regulation by advancing the design concepts to provide an inductive bias towards biophysically meaningful interactions
(2) Develop cutting edge model interpretability tools to distill knowledge learned by high performing deep neural networks.
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 deep learning frameworks (e.g., TensorFlow, PyTorch, or JAX) 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 firstname.lastname@example.org.
We have openings for graduate students at CSHL and Stony Brook University. Email email@example.com to discuss rotatation opportunities.