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Dr. Darius Bunandar, the Boston University team is led by Prof. Ajay Joshi, and the Harvard University team is led by Prof. Vijay Janapa Reddi. Role Our team has two postdoctoral researcher openings
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Technologies Programme and is a five-year project with £22.4 million total funding for a consortium of 17 institutions and over 50 research groups. The task of the theory group led by Prof Kyriienko
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, once the codes have been tested and validated, the work will involve performing simulations of materials for energy storage (batteries, supercapacitors), in collaboration with our partners in Japan (Prof
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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Assistant (Predoc) in the group of Univ.- Prof. Hajo Boomgaarden, PhD. Communication Science is an integrative social science characterized by methodological diversity, with a focus on indirect public
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(IOPP) at Central China Normal University (CCNU) invites applications for a postdoctoral research position in lattice gauge theory, with an emphasis on computational and algorithmic advancements
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 18 hours ago
Deadline: none (posted 2024/11/01) Position Description: Position Description Led by Prof. Fabio Boschini, the time-resolved ARPES (TR-ARPES) laboratory at the Advanced Laser Light Source (ALLS) user
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of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of research interests
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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join
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algorithms for the scanner using machine learning and deep learning. Qualifications: The position requires some background in machine learning, optimization, and deep learning. Some familiarity with MR physics