103 parallel-and-distributed-computing Fellowship positions at Harvard University in United States
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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, computer science, engineering, or related fields. Experience in relevant research topics is a plus but not required. Contact Information: Andrea Henderson Contact Email: amhenderson@seas.harvard.edu Special
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courses. The program serves as an ideal bridge between college and graduate school for students interested in empirical economics. Most previous fellows have gone on to top Ph.D. programs. Salary and
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Details Title Postdoctoral Fellowship in Power and AI Systems School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science/ Electrical Engineering
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or computational research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and manuscripts, participate in teaching and mentoring of lab members as
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January 11, for awards is February 1, and for the internship program is February 15. Undergraduate Students Graduate Students and Advanced Undergraduates Post-doctoral Fellows Early-Career Scholars (from
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an atlas of prokaryotic immune strategy in the global oceans University of Southern California, laboratory of Jed Fuhrman 2018 B. Cael, Ph.D. Testing a distributional theory for the sinking flux of marine
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)colonial Indigenous settings in the USA. Responsibilities Under the supervision of Prof. Joseph Gone, Faculty Director of the Harvard University Native American Program, and in collaboration with regional
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to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories and to develop approaches to predict and monitor