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and setup: Within the project, we follow a multidisciplinary collaborative approach for which we are have recruited 3 PhD students focusing on material science, advanced in vivo imaging and computation
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for the position. An application for enrolment should first be submitted after an appointment is made and the supervisor(s) will help with this procedure. The candidate must be enrolled as a PhD student within 3
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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processing modules, notably with the PyNX software (http://ftp.esrf.fr/pub/scisoft/PyNX/ ); Support ESRF beamlines exploiting coherent X-ray imaging techniques; Conduct an original research project exploiting
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Website https://www.academictransfer.com/en/jobs/357264/postdoc-position-in-microbubble… Requirements Specific Requirements A PhD degree in Applied Physics, Electrical Engineering, Biomedical Engineering
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procedure Are you interested in this vacancy? Please apply no later than 28 February 2026 via the application button and upload the … Where to apply Website https://www.academictransfer.com/en/jobs/357690/phd
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Neuroscience, or another related field by the start date. Prior experience using computational techniques is preferred. Application Procedure: Apply online at https://jobs.virginia.edu/us and search for
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application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context of medical imaging Development, implementation and validation of AI tools and
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-leading center for research and innovation in medical imaging, image analysis, and biomedical engineering. Our interdisciplinary research brings together engineers, computer scientists, physicists, and
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The successful candidate will lead and contribute to research activities focused on nanoscale magnetism and spintronic materials, with a strong emphasis on advanced TEM-based magnetic imaging, data interpretation