Sort by
Refine Your Search
-
Public Health Academic Pipeline Program in Maternal and Child Health (MCH) of the Harvard T.H. Chan School of Public Health (HSPH) invites applications for a full-time postdoctoral training fellowship
-
of Public Health is seeking a postdoctoral fellow in maternal health. The MCH Public Health Academic Pipeline Program in Maternal and Child Health (MCH) of the Harvard T.H. Chan School of Public Health (HSPH
-
cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and
-
and Applied Sciences Department/Area Electrical Engineering/Computer Engineering/Computer Science Position Description Project Deep learning plays an essential role in the operation of an autonomous
-
, Biostatistics, Computer Science, Statistical Genetics, or a related quantitative field (by the time of appointment). Strong background in statistical or machine learning methodology, optimization, or high
-
effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
-
effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
-
assessment, and ambulatory behavioral assessments to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories
-
with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy researchers. The successful candidate will lead development of variable importance measures – including
-
, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance is