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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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programme cohorts. Facilitating collaboration between academic staff, students, and external stakeholders to ensure smooth and effective programme delivery. Supporting dissemination, evaluation, and quality
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? Then the Department of Electrical and Computer Engineering invites you to apply for a 2 year postdoc position bridging research with industrial implementation and innovation. Expected start date and
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? Then the Department of Electrical and Computer Engineering invites you to apply for a 2 year postdoc position bridging research with industrial implementation and innovation. Expected start date and
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Job description - Developing device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. - Exploring hardware-level
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neuroscience, objective measures of auditory function, computational models of hearing, hearing-instrument signal processing, and multi-sensory perception. Our goal is to advance the understanding of the human
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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Postdoc Position in Models of Quantum Programming Languages (Sapere Aude: DFF-Research Leader Pro...
The Department of Mathematics and Computer Science at the University of Southern Denmark, Odense, invites applications for a postdoctoral research fellowship in models of quantum programming
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will