737 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" positions at Harvard University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
the Department of Molecular and Cellular Biology at Harvard University, we research and teach how the collective behavior of molecules and cells forms the basis of life. We are driven by a passion for discovery
-
in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
-
analysis. FlyBase is increasingly integrating artificial intelligence and machine learning tools into its curation workflows. The ideal candidate will be open-minded and enthusiastic about exploring AI
-
on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
-
where innovation, continuous learning, and work-life balance are valued. Learn more about the School’s mission, objectives, and core values , our Principles of Citizenship , and about the Dean’s AAA
-
-grad or MS level with a desire to research and learn more about biomedical research, multi-omic integration analytics and machine learning. In this role you will produce highly impactful biomedical
-
, 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
-
. Rather than being tied to a single lab, the RSE will provide shared, cross-project engineering support—helping multiple teams accelerate discovery by building and optimizing machine learning infrastructure
-
, flexibility, and creative problem-solving are essential. Strong computer skills, including proficiency in Excel, and ability to quickly learn new technology. Additional Information Standard Hours/Schedule: 40
-
Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic