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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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, integrate device engineering with clinical workflows, and apply artificial intelligence and machine learning for automated image and signal analysis, tissue classification, and real-time diagnostics
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, Engineering, or a closely related discipline. You will be a materials or physical scientist with a strong track record in applying deep learning to computer vision problems, ideally within battery
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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semimetals, magnetic monopole fluids, quantum spin liquids and exciton fluids. • Data Management, Analysis & Machine Learning Knowledge and experience in high volume image-array data acquisition and management
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related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with transformer architectures (e.g., ViT
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. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management
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University Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here, and learn more about Working in Lund , Moving to Lund and Living in Lund
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engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being
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) on the topic of surrogate optimization for supercritical fluid extraction / supercritical fluid chromatography (SFE/SFC). There will be the option to teach courses in the IMSE Department. Eligible candidates