110 postdoc-computational-biomedical-engineering Fellowship positions at Harvard University
Sort by
Refine Your Search
-
Details Title Postdoctoral Fellow in Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Bioengineering Position Description Professor Jia Liu and
-
with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
-
)colonial Indigenous settings in the USA. Responsibilities Under the supervision of Prof. Joseph Gone, Faculty Director of the Harvard University Native American Program, and in collaboration with regional
-
background in biological and/or biomedical sciences. Willlingness to work with rodents is required, but prior experience in rodent work is not required. Prior experience in reproductive biology is not required
-
Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
-
January 11, for awards is February 1, and for the internship program is February 15. Undergraduate Students Graduate Students and Advanced Undergraduates Post-doctoral Fellows Early-Career Scholars (from
-
of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
-
that converts your CGPA to a 4.0 scale. This can be done using a GPA conversion tool, such as Scholaro’s GPA Calculator , or by submitting a credential evaluation report from a service such as WES or ECE , which
-
the Mellon Foundation’s Humanities in Place program, Dumbarton Oaks invites applications for an early career postdoctoral fellow in environmental history with a research focus on race, indigeneity, settler
-
and Regenerative Biology has an exciting and broad multiomics program focused on brain aging. Approaches will include experimental and computational efforts across multiple labs at Harvard's Faculty