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Field
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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crystallization happens in a device and how does this impact power output? How can Magnetic Resonance Imaging (MRI) and X-ray Computed Tomography (CT) be used to visualize and analyze in-situ processes (e.g. phase
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collection activities. Supervision will be provided by academics from various disciplines specializing in biomechanics, image processing, and computer vision, alongside orthopaedic surgeons and academics.
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: Master’s degree in computer science, computer/software engineering, applied mathematics, artificial intelligence, or a related field. Strong skills in deep learning (e.g., PyTorch/TensorFlow). Experience in
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prototype and validate your research directly in the field. Integration into a dynamic, multidisciplinary team (engineers, computer scientists, animal scientists, veterinarians). Collaborations with
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science, engineering, physics, mathematics or a similar domain. There is a strong preference for an applicant with a biomedical background. Experience with medical image processing, histopathology, computer vision
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Open to: UK fee eligible applicants only Funding providers: EPSRC and LaVision UK Ltd Subject areas: Biomedical Engineering, Experimental Mechanics, Image-Based Measurements, Biomechanics Project
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and Engineering at the University of Luxembourg, and follow a vibrant PhD program that includes training in transferable skills, support for career development, lectures and teaching by international
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institutions within Luxembourg. The PhD student will be enrolled in the Doctoral School in Science and Engineering at the University of Luxembourg, and follow a vibrant PhD program that includes training in