76 distributed-computing-associate-professor Postdoctoral positions at Stanford University
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scientific domains. Preferred Experience: Strong candidates may also have experience with: Large-scale neuroimaging datasets. GPU-based model training and distributed computing. Brain connectivity modeling
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. Lynette Cegelski is the Monroe E. Spaght Professor of Chemistry and Courtesy Professor of Chemical Engineering at Stanford. She is affiliated with the Stanford Biophysics Program, Sarafan ChEM-H, and the
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Huang, Ph.D., Associate Professor in the Department of Cardiothoracic Surgery at Stanford University School of Medicine. We are interested in studying the role of cell-biomaterial interactions that 1
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distribution. Both projects will develop the Fontan emulator to be patient-specific, MRI compatible, computer controlled, and quantitatively evaluated using advanced bench-top, CFD/FSI simulation, and MRI-based
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of reaction pathways, residence-time distributions, heat and mass transfer, and particle or catalyst evolution. Establish quantitative mass, carbon, and energy balances across the reactor system. Relate reactor
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the occurrence frequency of atmospheric rivers? What is the predictability source for atmospheric rivers at the sub-seasonal timescale? The successful candidate will work closely with Professor Da Yang and will
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, with additional mentorship from Professor Bobby Bartlett. The program is structured to support the development of a strong research pipeline, including the opportunity to coauthor work with Professors
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global research capacity through partnerships and training Position Description The QoLA Lab is seeking a highly motivated postdoctoral scholar to contribute to an ambitious and growing program of research
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and Geographic Medicine, Stanford School of Medicine, with co-advising by Dr. Mathew Kiang, Assistant Professor of Epidemiology. The project involves developing a rigorous causal framework for assessing
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microscopy. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master