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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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high-speed data traffic over very long distances, and they collectively constitute the so-called Internet backbone. By harnessing recent advances in machine learning and artificial intelligence (AI
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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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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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PhD student with an interest in neuro-symbolic AI (machine learning and symbolic methods) to work as a researcher on this project, which will include both implementation work and experimentation. It is
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responsibilities The position comes with enrollment in the PhD program for Computer Science and Engineering, designed for 5 years. As a PhD student, you acquire the skills and knowledge to conduct independent
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computing and programming skills (e.g. Python and R), experience in the Linux/UNIX computer environment, and, preferably, previous experience in working with machine learning and/or artificial intelligence
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scientific conferences - Study PhD courses - Teach courses within the scope of Production Systems - Develop your pedagogic and teaching skills, while developing a personal pedagogical portfolio Please read
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to research projects - Publish research results in scientific journals and at highly ranked, international scientific conferences - Study PhD courses - Teach courses within the scope of Production Systems
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Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD student position in Formal Verification of Autonomous Cyber-Physical Systems Autonomous cyber-physical