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Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Horizon 2020 Reference Number 101226717 Is the Job related to staff position within a Research Infrastructure? No Offer
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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Deadline: All year round How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD project is open to home students; the successful candidate will receive an annual tax free stipend based on the UKVI amount (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend...
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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platforms, and/or those proposing to use quantitative/computational methods will be given preference. Applicants are also encouraged to think about the societal impact of their research, and for example
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or potential damage to the rail surface. The Research: This project aims to transform this process by developing a novel machine learning (ML) tool and utilising cutting-edge machine learning algorithms
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for experimental work, conference travel, or the latest computing gear, we’ll make sure you have the resources to succeed. Launch Your Career: Our graduates have landed senior roles in top industries, thanks to
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cancer-focused disciplines. The TRACC+ Programme is funded by Cancer Research UK and NHS Education for Scotland and commenced in 2019. Vacancies are available within TRACC+ for trainees seeking doctoral
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the opportunity to transition into a PhD programme based on performance and mutual agreement. The Cambridge Institute for Medical Research (CIMR) is located on the Cambridge Biomedical Campus and it is
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research, and an active programme of research seminars for both students and staff. The successful candidate will join a dynamic, supportive, and collegial faculty, recognised for excellence in teaching