Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
addition to carrying out bench research using electrophysiological recording, the successful candidate will be expected to help develop data management software for managing and analyzing large volumes
-
molecular and phenotype data. Including code that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of
-
of optimizing pipelines for large-scale genomic projects. Special Instructions Required documents: CV Research summary of PhD work. Cover letter describing your interest in the lab and initial ideas for new
-
large administrative or claims data (e.g., Medicaid, commercial claims, or similar) Clear scientific writing and communication; a track record of publications Special Instructions Please include: · CV
-
salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines
-
) that impacts humans on all levels: from the single cell to populations, providing a rich substrate to do novel work. In this role you will gain experience developing approaches to research and analyze large
-
lab group meeting (journal readings, in progress research talks, visiting speakers), and helping affiliated PhD and undergraduate students gain access to and work with the Cebu data. The Postdoc will
-
, and statisticians—on projects that bridge methods, policy, and practice. This role will involve intensive analysis of claims data and related large administrative datasets to support policy-relevant
-
position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
-
such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health-related datasets