Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
agreement. Each fellow will work with 1-2 faculty mentors on research projects that cover a broad range of environmental and agricultural economics topics and methods. Faculty mentors for this program will
-
interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
-
phenotypes. The lab uses a variety of experimental (functional genomic, targeted genetic) and computational (bioinformatics) tools on human and mouse tissues and using in vitro methods on human cells
-
computational efforts across multiple labs at Harvard’s Faculty of Arts and Sciences and Medical School. As part of this effort, the Rubin lab is implementing new methods of studying aging in vitro using brain
-
. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
-
Program is a transformational award for early career researchers who show exceptional promise of becoming outstanding leaders in academic science, making foundational discoveries while building an inclusive
-
computational efforts across multiple labs at Harvard’s Faculty of Arts and Sciences and Medical School. As part of this effort, the Rubin lab is implementing new methods of studying aging in vitro using brain
-
with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
-
learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
-
health data related field preferred 2+ years of relevant experience Enthusiasm for and experience working with complex real-world datasets Implementation of computational methods for big data Solid