48 parallel-computing-numerical-methods Postdoctoral positions at Pennsylvania State University
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: Your role at the lab is to investigate the behavior of individual molecules and bio-molecular condensates in living cells. You will use and develop the imaging and computational methods that to visualize
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University, invites applications for a Postdoctoral Scholar position in the research group of Dr. Xiaoyue (Maggie) Niu. Potential research projects include (but are not limited to) work on methods and theories
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presenting at seminars and national conferences Assisting in lab management and supervision of junior members Developing new research methods and contributing to other projects in the lab Qualifications: Ph.D
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methods, stochastic control processes, dynamic programming, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong programming skills
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of physics beyond the Standard Model, using analytical and computational approaches. The successful applicant will join Dr. Carlos Blanco's research group with significant academic freedom to pursue
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must be ready to conduct research involving the design of novel behavioral interventions, conduct human studies, and build computational models to implement existing behavioral paradigms such as Just In
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Engineering and should have experience in materials characterization, numerical modeling and statistical analysis, and welding metallurgy. The Pennsylvania State University’s College of Earth and Mineral
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and computational studies of mechanics of materials, with an emphasis on fracture prediction. In addition, the postdoc will contribute to and/or lead manuscript preparation and project reporting
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management and supervision of junior members Developing new research methods and contributing to other projects in the lab Qualifications: Ph.D. in biomedical sciences or related field Publication record in
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Sriperumbudur. Potential research projects include (but are not limited to) developing theory and methods for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows