Sort by
Refine Your Search
-
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
-
into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
-
, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
-
scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
-
into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
-
work as part of a larger team to assist with collecting and analyzing data gathered from human subjects, both in field, clinic and lab studies as part of evaluations of the technology. A large part of
-
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
-
interatomic potential to incorporate materials response . Resulting models are implemented in LAMMPS and are used to perform ML-accelerated large-scale dynamics simulations to investigate the evolution
-
into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
-
to a deeply decarbonized and reliable energy system. The Postdoctoral Fellow will work closely with the project directors and collaborators to develop data-driven and economically grounded frameworks