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We are looking for a Senior Lecturer in Fine Arts with a specialisation in installation, digital imaging and drawing, including administrative duties as Director of Studies. As a Senior Lecturer in
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or explainable AI or safety). Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models. Experience in analyzing multimodal data (e.g., text, sensor
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computational photography. The specific focus is on research and development of methods and mathematical analysis relevant to perception, image formation, and computer graphics. The general focus is on research
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developing complete models. Example applications include microscopy image data, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics data, and
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learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
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, particularly in applying advanced screening tools, such as high-content imaging (Cell Painting) to uncover effects of exposure to (nano)particles and chemicals. The position is hosted by the School of Medical
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specialist qualification. The clinic is equipped with a QHorse, a Qualisys system for objective lameness assessment. At the University hospital we have a diagnostic imaging clinic, equipped with large animal
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love to create engaging content. This means you should have content creating skills, such as writing, photography, graphics and filmmaking and experience of communication in social media (image, film and
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or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide data analysis support to data
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on the effects of plant-based proteins and dietary fibers on intestinal-, metabolic- and mental health. The project applies microbiome analysis, metabolomics, functional brain imaging, and nutritional analyses