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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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to funding restrictions this PhD position is only available to UK nationals. As this position is sponsored by the MTC, any successful candidate would need to pass the sponsors own security checks prior
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grant Specified use +3 - to cover the full PhD Humanitarianism & Conflict Response programme Tenable period 3 years full-time or 6 years part-time. Continuation of award Continuation of the award is
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and Paralympic games cycles where the cycling team have seen unparalleled success on the track. We are pleased to be able to offer a PhD opportunity working alongside Team GB cycling and Shell to
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community of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Appointment at Research Associate level is dependent on having a PhD (or equivalent experience
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD
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edaphic conditions in this island group. Plant material is already available so the focus is on laboratory and computing techniques. During the placement you will be taught DNA extraction, DNA data handling
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an original programme of research working with ecologists Dr Fay Voller , Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science . This PhD is