Our research combines machine learning and biology with the broad goals of data integration, model interpretation, and method development for biological and biomedical applications.
光粒加速器-快连加速器app
The lab is looking for highly motivated students, with strong computational skills, who are excited about developing data-driven approaches to solve important problems in biology and health sciences.
If you are interested in joining the lab or collaborating with us, please e-mail ritambhara@brown.edu.
Required skills for lab members include basic UNIX/Linux competency and programming ability (preferably in python). Coursework or project experience in machine learning and/or deep learning is highly preferred.
Students at Brown, who are interested in joining the lab, are recommended to first attend the Deep Learning in Genomics course in the Fall (Graduate) and Spring (Undergraduate).
光粒加速器-快连加速器app
Assistant Professor
Computer Science
Ph.D. Students
(co-advisor: Erica Larschan) Computational Biology
(Crawford Lab)
Computational Biology
(Sandstede Lab)
Applied Mathematics
(Joining deferred till Spring ’21)
Computer Science
(Joining deferred till Spring ’21)
Computer Science
Masters Students
Computer Science
(Concurrent Masters Program)
Computer Science
Undergraduate Students
(UTRA Summer ’20 Awardee)
(SPRINT Summer ’20 Awardee)
光粒加速器-快连加速器app
Elliot Kang (Class ’20)
David Inho Lee
光粒加速器-快连加速器app
We are located in the Center for Computational Molecular Biology at 164 Angell St. (3rd Floor)
The most dangerous phrase in the language is, “We’ve always done it this way.” – Grace Hopper
