153 phd-scholarship-for-solid-mehanical-engineering-in-image-processing PhD positions in Sweden
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We are currently offering a PhD student position focused on developing new AI-driven methods for molecular engineering, with an emphasis on the discovery and design of solid polymer electrolytes
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We are currently offering a PhD student position focused on developing new methods for molecular engineering that leverage live-cell imaging data and artificial intelligence (AI). The position is a
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Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and
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Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and
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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning
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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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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
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background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or
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We are now looking for our new PhD who will join us in our poject in ELLIIT , Linköping University. Your work assignments The selected candidate will conduct cutting-edge research on unconventional
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as