61 parallel-computing-numerical-methods-"Prof" positions at Chalmers University of Technology
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description The specific subject of the research position is to study vector bundles with singular metrics, in particular in connection with L2-methods. This is nowadays standard techniques for line bundles
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of recycled aluminium. More specifically, the project will focus on advanced numerical methods to understand how defects and different microstructures affect the strength of mega-cast components. As a PhD
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods
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of quantum computers, and resource theory for quantum computation. They will carry theoretical studies using both analytical and numerical tools, in these subject areas. They will also interact with
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We invite applications for several PhD positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment of the Wallenberg Centre
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We invite applications for several postdoctoral research positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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division at the department of Electrical engineering at Chalmers. Here, a team of PhD students, post-docs and senior researchers are working on modeling and numerical optimization of problems in the areas
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the preservation of cultural and historical values, and contribute to accessible, high-quality housing. The project will apply qualitative and participatory methods such as focus groups, interviews and workshops. A
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reliable and sustainable components more affordably and more efficiently. Due to the complexity of the research, an integrated framework combining experiments, simulations, and data-driven methods is