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quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
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Science, Computer Engineering, Artificial Intelligence, Physics, Mathematical Engineering, Mechanical Engineering or similar. Relevant skills: Strong background in machine learning/data science. Deep knowledge
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also