31 condition-monitoring-machine-learning PhD positions at Chalmers University of Technology in Sweden
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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many research synergies coming together on the main thread of machine learning and Artificial Intelligence (AI). The successful candidate will join the newly established research group AI in
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systems. We will also conduct LCA and environmental impact assessments of our material and conduct user studies to acquire practical feedback on panel designs. The final biobased wall demonstrator
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at the same time so special. The originality of the experiments is in the combination of X-ray based scattering and imaging methods to monitor the changes at the particle scale during testing. Research
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the Division for Computer network and systems and the employment is placed with Chalmers University of Technology. Our research spans from theoretical computer science to applied systems development. We provide
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develop innovative remote sensing capabilities to monitor oceans, ice, vegetation, and natural disasters. Be part of a dynamic, international team shaping the future of environmental monitoring! About us At