Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
-
, or comparable research experience, along with significant experience in machine learning, computer programming, computational biological applications. A strong background in statistics and biology. Experience
-
interactions with local centres of excellence in artificial intelligence, machine learning, applied mathematics, and computational sciences Application Procedure We accept applications from students of any
-
, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
-
profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
-
in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
-
of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning
-
environments will provide the successful candidate with opportunities to learn from a large network of talented professionals. Prof. Mariam Jamal-Hanjani is Principal Investigator of the TRACERx study at UCL