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of a collaborative team, led by Dr Sarah Morgan at the School of Biomedical Engineering and Imaging Sciences. The School is a world leading centre of expertise in AI for healthcare, providing
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configurations. Design, prototype and validate EM sensors and arrays for defects and materials. Develop sensor-interface electronics and multi-channel data acquisition, improving the real time hardware and
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researcher with strong skills in artificial intelligence, machine learning, deep learning, and computer vision, with the ability to apply these methods to ultrasound image/video analysis and biomedical data
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or the application process, please contact the HR Office at the Department of Engineering: [email protected] , +44 (0)1223 332615. Please quote reference NM51187 on your application and in any correspondence
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project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris Papageorghiou (Department of Women’s and Reproductive Health). This exciting and ambitious research aims
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tidy records of protocols, cell passage, sample processing, reagent preparation, imaging runs and experimental support activity. Work with fungal engineering and bioelectronic interface teams to ensure
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autonomous operation within the gastrointestinal tract. Objective 4 – Validate capsule technologies in representative gastrointestinal environments Fabricate prototype devices and evaluate their performance
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are looking for: Skills/ experience required for this exciting role include: Essential Postgraduate degree (MSc) in computer science, AI, or similar. Demonstrable competence in machine learning, medical image
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Primary Supervisor: Dr. Dennis Fitzpatrick Cardiovascular disease remains a major global health challenge and continues to drive innovation in medical technology. Cardiovascular devices form
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immune cells, proliferation assays, human sample processing or high-resolution imaging of proteins on live cells would be advantageous. You must have a proactive and adaptable approach to work and