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Job Description Are you a skilled and field-ready researcher with a passion for marine monitoring using many different methods and techniques ranging from diver observations to integrating remote
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hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project
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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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to prototype validation and measurement activities. Document design choices, trade-offs, and experimental results in high-quality publications. The position offers the opportunity to establish an independent
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Arbøll, e-mail: tpa@hum.ku.dk . Application Submit the application online in Adobe PDF or Word format. Please click on the “Apply now” icon at the bottom of this page. The application must be written in
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al