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Field
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We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
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date. Additional Required Qualifications Relevant Ph.D. in Electrical Engineering or Computer Science or related fields, or a relevant Master's Degree and required years of relevant experience. Strong
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
., Architectural, Electrical, Mechanical or Industrial Engineering, Autonomous Systems, Computer Science, Medical Engineering, and Human Psychology) Excellent background in the design, creation, and testing
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-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning
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Job Description Are you passionate about neuromorphic computing and hardware design? Do you want to contribute to the next generation of brain-inspired computing systems for healthcare applications
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to join a cutting-edge research project at the intersection of microelectronics and quantum computing. As the quantum computing field rapidly advances toward large-scale, fault-tolerant systems, one
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the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/research-training-program-scholarship#scholarship-details Be inspired, every day Drive
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 20 hours ago
Dresden University of Technology Course location Dresden In cooperation with Dresden University of Technology Teaching language English Languages The programme is conducted in English. Full-time / part-time
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research focuses on the study of quantum magnetism at the atomic scale. We build artificial quantum architectures from single atoms and molecules on surfaces and on probe tips, control their spin states, and
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools