143 computer-"https:" "https:" "https:" "https:" "UNIV" "UNIV" positions at Ulster University
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waiting lists, support and optimise programme uptake and outcomes, using observational questionnaires and exit interviews. Methods An in-depth analysis of existing Pulmonary Rehabilitation programmes in
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for at least the three years preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading
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date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis
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three years preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a
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preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a
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preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a
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was established. This is a £55M programme funded by Department of Economy NI and Industry partners, managed by the UKRI Strength in Places programme. This programme is a collaboration between regional Life and
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supported by PEACEPLUS, a programme managed by the Special EU Programmes Body (SEUPB) involving a range of partner organisations. NWCAM2 is an initiative seeking to help small and medium sized enterprises
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. The proposed PhD is a partnership with Age NI. Age NI have led two important online programmes recently. The Good Vibrations programme was a men’s health programme aimed specifically at men aged 50 and over. It
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vision systems addressing an urgent industrial challenge with immediate, large-scale impact. The project will take existing knowledge in computer vision and deep learning and apply it directly to a