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This PhD position offers a unique opportunity to dive into the exciting area of reinforcement learning within the broader landscape of AI and machine learning. As a candidate, you'll have the chance
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--1-12937 Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you driven by the challenge of advancing the boundaries of machine learning and computer vision
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Are you driven by the challenge of advancing the boundaries of machine learning and computer vision? Join the Computer Vision Group as a PhD student, and be at the forefront of groundbreaking
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Are you passionate about pushing the frontiers of machine learning, computer vision, and their applications in medical imaging? Join the Computer Vision Group as a PhD student specializing in deep
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the structural, electronic (and photoluminescent), and dynamical properties of the 2D HOIPs, to compare with the experiments. In particular, machine learning force field (MLFF) will be exploited to study finite
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them, and conduct experiments with modern machine learning techniques (e.g., deep neural networks, graph neural networks, or active learning) with the goal of predicting the performance impact of code
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on the software side: - Warm-start for VQAs using the underlying structure of molecules and their Hamiltonians – to minimize the number of quantum-classical computer cycles needed for convergence. - Learning
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, a combination of theory, numerical modeling and the application of machine learning for reduced physics and surrogate models are used. The research will be performed in an international environment
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researchers working in AI across Sweden and abroad. Major responsibilities We are looking for a PhD student with an interest in neuro-symbolic AI (machine learning and symbolic methods) to work as a researcher
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at the division are organized in two research units: power grid and components and electrical machines and power electronics. In the research unit on electrical machines and power electronics, we are about 30