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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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, and who have strong grounding in the methods and practice of oral history. The holder of this postdoc will teach two courses a year, one an introduction to oral history method and practice, and one
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motivated postdoctoral researcher with strong background in signal processing or MR physics with experience working with MRI data and MR scanners. Knowledge of machine learning methods is a plus. The postdoc
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retirement plans with university match Learn more about working at UNL: https://go.unl.edu/aboutus As an EO employer, the University of Nebraska considers qualified applicants for employment without regard
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education Generous retirement plans with university match Learn more about working at UNL: https://go.unl.edu/aboutus As an EO employer, the University of Nebraska considers qualified applicants
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UiO/Anders Lien 24th March 2026 Languages English English English Join the inclusive University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD
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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | 2 months ago
Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of Machine Learning for Infection and Disease is looking for a Postdoc (f/m/d) on Generative AI
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience