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Your Job: We are offering a PhD position dedicated to the advancement of cryo-EM image analysis methods at the interface of Structural Biology and Electron Imaging at the Forschungszentrum Jülich
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of image analysis and machine learning with a minimum of 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural
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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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HRS2025/180 Investigador en procesado de imagenes médicas / Researcher on medical imaging processing
radiologic, histopathologic and clinical data biomedical image processing using deep learning techniques. Where to apply E-mail mj.ledesma@upm.es Requirements Research FieldEngineering » Biomedical
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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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& Applications. The SPARC group in SnT is pursuing research on signal processing applications in radar and communication systems in partnership with national and international academic and industrial collaborators
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positions to pursue PhD projects in the areas of biology, chemistry, physics, mathematics or computer science. We are looking for young scientists with a vivid interest in interdisciplinary projects to image
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Engineering and Cybernetics VSB -Technical University of Ostrava. The successful candidate will carry out research in the field of Biosignal processing and medical images processing under supervision of prof
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images processing under supervision of prof. Marek Penhaker (https://orcid.org/0000-0001-9527-4642 ). This position requires knowledge related to modern methods for biosignal processing, preferably medical
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HRS2025/128 Investigador en procesado de imagenes médicas / Researcher on medical imaging processing
de algoritmos de segmentación de imágenes biomédicas, comparación de métodologías con y sin restricción de forma. ---------------------------------- Development and validation of biomedical image