178 parallel-computing-numerical-methods-"https:" Fellowship positions at Harvard University
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computational approaches. See our lab web page (https://projects.iq.harvard.edu/gaudetlab ) for more information about our publications and research interests. Basic Qualifications Candidate must hold a PhD in
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postdoctoral fellow to explore new methods for embodied intelligence in soft and reconfigurable robots. Basic Qualifications Doctoral Degree in Electrical Engineering, Mechanical Engineering, Bioengineering
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dynamics, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance
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the Senior Director of Labs (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our
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, 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
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collaborations among operations researchers, statisticians, and computer scientists to overcome the methodological challenges posed by the misalignment between historical methods underpinning modern data science
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methods into clinical applications to enhance oral health care. Under the supervision of principal investigators, the selected candidate will collaborate with a multidisciplinary research group, working
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environmental and agricultural economics topics and methods. Faculty mentors for this program will include Ishan Nath , Anna Russo , Wolfram Schlenker , and Charles Taylor . An important goal of the fellowship is
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computational efforts across multiple labs at Harvard’s Faculty of Arts and Sciences and Medical School. As part of this effort, the Rubin lab is implementing new methods of studying aging in vitro using brain
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected