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Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Machine Learning in IoT Edge Devices – DTU Electro Kgs. Lyngby, Denmark Job Description We invite applications for a PhD
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available from 1 October 2024 or later. You can submit your application via the link under 'how to apply'. Title PhD position in machine learning to predict nitrogen leaching at field level Research area and
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Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Machine Learning Techniques for Spectral Shaping of Ultra-Broadband Optical Frequency Combs - DTU Electro Kgs. Lyngby
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Two fulltime post doc positions in Theory of machine learning are available. The post docs are under the supervision of Professor Kasper Green Larsen, Aarhus University, Denmark. The focus
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The PhD project is part of the DFF (Independent Research Fund Denmark) granted research project“Audio Only VR for Blind Gamers”. The research project investigates audio-only Virtual Reality for blind gamers, including their needs and interests, diversity in motivation, and usage to better...
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. To overcome this challenge, neural architecture search and other ideas within the general field of automated machine learning have been proposed. We seek one or more PhD students(employed as PhD fellow if you
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on cutting edge machine learning methods? If you are establishing a career as a researcher in machine learning, and you are motivated to work with the latest methods for quantifying uncertainty in neural
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of novel computer vision methods capable of robustly detecting AUs. Next, the focus will be on novel AI methods for classifying normal vs. pain vs. stress faces. Lastly, head pose detection of horses in
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operations research, machine learning, and decision-making frameworks, with the ultimate goal of creating real-time autonomous systems that are not only trustworthy, but also adaptive when faced with
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of specific 2D functionalization strategies, we have a broad and flexible focus when it comes to the employed methodologies (empirical models, DFT, many-body perturbation theory, machine-learning) the target