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, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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; 5)Contributing to the co and extra-curricular activities of Keller. - Applicants must hold or expect to have a doctoral degree in civil, structural, architectural or mechanical engineering, physics
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, nanolithography, etching, and deposition and experience in applications of nanostructures is a plus.3. Experimental nanophotonics. Candidates should have significant experience in nanophotonic devices (including
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: 277344492 Position: Postdoctoral Research Associate Description: The group of Prof. Aditya Sood in the Department of Mechanical and Aerospace Engineering and the Princeton Materials Institute at Princeton
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experience in scholarly research and a strong commitment to excellence in education are encouraged to apply. A PhD in Materials Science, Optics, Physics, Chemistry, Electrical, Chemical, Mechanical, Civil
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Environmental Engineering and the Form Finding Lab; - Leading outreach efforts and developing and writing research proposals. Minimum qualifications: - Doctoral degree in civil, structural, or mechanical
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of mass spectrometric datasets (https://www.nature.com/articles/s41592-021-01194-4 ). The research is computational in nature but involves close interactions with experimental collaborators. Many
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Laboratory (NAP Lab), led by Dr. Sabine Kastner at the Princeton Neuroscience Institute. The lab studies neural mechanisms of cognition in the primate brain. Intracranial recordings from human epilepsy
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, nanolithography, etching, and deposition and experience in applications of nanostructures is a plus.3. Experimental nanophotonics. Candidates should have significant experience in nanophotonic devices (including
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of reinforcement learning in the brain and leverage these models to assist the experimental groups with experimental design and multimodal data analysis of neurophysiological, causal, and behavioral data