26 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" Postdoctoral positions at Pennsylvania State University
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focus and interest. Fellows will work directly on research projects of CGNE-affiliated faculty, pursue independent research activities in line with their developing program of research, and engage in
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collaboration and leverage University resources Communicate with internal management, program sponsors, and other stakeholders. Develop ideas and proposals for potential new programs Minimal requirements include
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. The successful candidate will work with Prof. Zhiqiang Mao on a quantum materials research program focused on the discovery and synthesis of novel quantum materials, including magnetic topological materials and
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. The successful candidate will work with Prof. Yinming Shao on a quantum materials research program focused on the optical studies of novel quantum matter, including topological materials and magnetic
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to the research program led by the Penn State numerical relativity group. There will also be ample opportunity to collaborate with other members of the Institute for Gravitation and the Cosmos, which includes
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focusing on mobile health phenotyping and environmental influences. This position will be directly involved in a diverse range of participant, lab, and university-facing activities across multiple teams
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the position is filled. Application Materials: Applicants are requested to submit the following: A letter of application A research statement describing: research interests and career plan planned research
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mission is to conduct interdisciplinary research that contributes to the evidence base needed to inform successful childhood obesity prevention programs that can then be disseminated to public health and
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programming basics. Additional Information The start date is flexible, with September 1 2025 being the earliest date. Interested applicants should submit a pdf with a CV, a statement of research interests, and
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independently and collaboratively. Preferred Qualifications A strong background in AI/machine learning, mathematical modeling, and programming. Extensive practical experience in AV development, testing