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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month ago
of PhD certificate or diploma; Detailed Curriculum Vitae; Motivation Letter. The submission of applications is digital, in pdf format, from 02/03/2026 to 15/03/2026, in the following link: https
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of cancer treatment for patients as well as reducing workload for clinicians. Collaborate with experts in AI, data science, and medical imaging to develop integrated solutions. Engage in translational
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medical center, offering opportunities to support investigator-initiated projects, contribute to publications, and mentor trainees. Responsibilities Analyze gynecological and obstetric imaging datasets
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& Sciences (SCMMS) provides an outstanding multi-disciplinary environment for the pursuit of cutting-edge cardiovascular and metabolic research (https://www.kcl.ac.uk/scms ). We study the fundamental molecular
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and teaching unit situated within the College of Medical, Veterinary & Life Sciences. It has recently been rated 4th in the UK and 1st in Scotland, REF 2021 research output in Times Higher Education
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School of Medicine Indianapolis Position Summary Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging
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closely related quantitative discipline. A strong and demonstrated track record in medical image analysis is mandatory. The applicant must have prior hands-on experience working with medical imaging data
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licensed medical care, including diagnosis, specialized surgical expertise in treating severe sleep disorders, treatment (including surgery or pre/post-surgical care where appropriate), case management, and
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project. The project will also employ a PhD student at Lund University, focusing on developing hybrid architectures for deep learning-based image processing and methods for multimodal medical data. We will