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Mobile Edge Computing (MEC) has emerged as a promising computing paradigm to support emerging high-performance applications by deploying resources at the network edge. However, most existing MEC
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Medical imaging is central to the diagnosis and management of lung and abdominal diseases, including lung cancer, pneumonia, liver disease, and gastrointestinal disorders. In real clinical workflows
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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-urban accessibility to health and socioeconomic outcomes. It will: Challenge the fixed-threshold paradigm by introducing the concept of the “N-minute city,” where N is a time variable that differs across
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challenges. Supervisor information: https://experts.exeter.ac.uk/41651-tarje-nissenmeyer https://experts.exeter.ac.uk/41625-george-datseris Ready to bridge mathematical sciences with complex ecosystems and
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welcome). Further information on this role can be found at https://exetermathematicsschool.ac.uk/life-at-ems/work-with-us/ . Applications to be returned to jobs@exeterms.ac.uk
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& Find Out More : To apply for this fully funded PhD Studentship or for more information, follow this link: https://www.exeter.ac.uk/study/funding/award/?id=5840 Application Deadline: 19 APRIL 2026 @ 23.59
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Project Description The next generation of signal processing, computing and artificial intelligence (AI) technologies will be unlocked by the close integration of electronics and photonics
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be required to complete a Temporary Worker Registration Form and conduct a right to work check. The work cannot start until these steps have been taken . The full temporary worker process can be found
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pathway to overcome the limitations of polymer-based membranes, offering superior thermal and chemical stability, enhanced mechanical robustness, and the potential for operation across wider temperature and