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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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Agents in Diagnostic Imaging - Eng-PhD-17-25 Engineering Biology-Enabled Sustainable Supply Chains - Eng-PhD-01-25 Real-time Powder Bed Defect Detection and Prediction using Texture-based Imaging and AI
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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Supervisors: Prof Ioan Notingher (School of Physics and Astronomy) Dr George Gordon and Dr Abdelkhalick Mohammad (Faculty of Engineering) Funding: fully-funded (stipend and PhD fees) Start date
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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commencing on the 2nd of March 2026 (online or in person, depending on the candidate’s location). The selected candidate will need to follow the regular PhD application process at the University of Nottingham
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
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11 Feb 2026 Job Information Organisation/Company University of Twente (UT) Research Field Engineering » Biomedical engineering Engineering » Microengineering Researcher Profile First Stage
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. Methods, 2024). The approach is still in its infancy; hence we need to drive the further development of the imaging technology, labeling agents and analysis approaches at the same time. To demonstrate
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages