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, modelling and machine learning to improve defect detection, classification and power loss simulations. Benchmarking field-acquired images with laboratory measurements. Publishing results in leading journals
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab
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total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities
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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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theyoftenfall short due to data limitations and model simplifications. Recent breakthroughs in data assimilation (DA) and machine/deep learning (ML/DL) arechanging the game. With new satellite missions like SWOT
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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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Job Description Do you want to do research on cutting-edge machine learning methods? If you are building a career as a researcher in machine learning and are passionate about working with cutting
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and