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tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier
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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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. The department has a strong community on related topics: research groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will
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automation, CAD design, programming, vacuum systems, machine learning and/or electronics is considered advantageous but not required Alignment with our core values What we offer Full-time, 4-year PhD funding
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Devices (QCD) group at the Department of Applied Physics. In this position you have a chance to make history by demonstrating some of the first experiments of the future quantum-computer technology that is
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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to you in order to be able to do systems identification and model process dynamics using traditional and advanced tools such as machine learning. Your role and goals You will work in collaboration with
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field (with a CGPA of at least 3/5) Experience (e.g. coursework, projects, etc.) in AI and machine learning, including understanding of various DNN architectures, training models, and applying them
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combustion CAD modelling capability to design and modify the facilities, such as nozzles, optical spray and combustion chamber, optical engine, etc. Matlab, Python, and other programming languages Machine