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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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bioinformatics, engineering physics, molecular biology, computer science, or a related field. You should have strong programming skills (e.g., in Python or R) and a keen interest in applying data-driven methods
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. These positions involve advanced numerical simulations and analysis of spacecraft data. The positions are full-time, 100% funded for four years and lead to a doctoral degree in Computational Physics. The expected
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postgraduate education in areas such as Information Processing Technologies, including Quantum Information and Computation, Optoeletronics, Physical Layer Security and Information Theory, Cybersecurity and
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our PhD programme, please visit our information page. We offer a fully financed position. Your time will be devoted to your doctoral studies (80%) including coursework and writing a doctoral thesis
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and