553 computer-science-quantum-"https:"-"https:"-"https:"-"https:" positions at Harvard University in United States
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
workshops to further develop research and communication skills. Basic Qualifications: Bachelor's degree in computer science or closely related field. Additional Qualifications: Demonstrated interest in
-
Details Title Postdoctoral Fellow in Biomedical Informatics (Cai Lab) School Harvard Medical School Department/Area Biomedical Informatics Position Description A Postdoctoral Research Fellow
-
Details Title HMS - Postdoctoral Fellow in Biomedical Informatics (DBMI) School Harvard Medical School Department/Area Biomedical Informatics-Quad Position Description The Department of Biomedical
-
Details Title HMS - Associate in Biomedical Informatics (Zitnik Lab) School Harvard Medical School Department/Area Research Position Description The Associate will engage in academic research and
-
computational bio/neuroscience principles with modern machine learning techniques. Basic Qualifications Ph.D. in a relevant field (e.g., computer science, ML, computational neuroscience, bioengineering
-
The Computational Science and Engineering Laboratory at Harvard University invites applications for postdoctoral position at the interface of scientific Computing and Artificial Intelligence for applications
-
Details Title HMS - Postdoctoral Fellow in Biomedical Informatics (Park Lab) School Harvard Medical School Department/Area Biomedical Informatics Position Description The candidate will have the
-
Details Title Postdoctoral Fellow in Thymic Engineering School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Bioengineering Position Description The Mooney Lab
-
Details Title Post-Doctoral Fellow in Chemistry and Chemical Biology (Liau Lab) School Faculty of Arts and Sciences Department/Area Chemistry and Chemical Biology Position Description The Liau Lab
-
Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of