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to the development of innovative solutions and algorithms to enhance 5G network capabilities. Work closely with the Principal Investigator (PI), Co-PI, faculty and research team to plan, track, and deliver project
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. The project seeks to develop mathematical models for allocation of critical resources during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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, whilst having experience with implementing Bayesian algorithms will be an advantage. A background in biology is NOT required. The post is for up to 6 months, to 31st March 2026. Additional funding is
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during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them. The selected candidate would disseminate their research by publishing in top-tiered
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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of the position is to pursue cutting-edge research in automata theory, and possibly at the interface with algorithms (fine-grained complexity). We will consider applications for employment on a part-time or other
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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research in the field of AI for healthcare autonomous systems. Activities on non-healthcare systems could occasionally be requested. • Undertake research from algorithm development to real time