80 computer-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Ulster University
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advanced AI/ML methods to neural and behavioural data to uncover the computational foundations of decision-making in humans and animals. Designing novel AI algorithms inspired by brain function, to improve
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record in astrocyte-neuron interaction modelling, published in Frontiers in Computational Neuroscience, PLoS Computational Biology, Neurocomputing, and IEEE Transactions on Neural Systems and
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approaches often provide only limited insight into these effects. This project will use advanced computer simulation, informed by post-operative scans and patient movement data, to understand how variations in
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through the vessels and how diseases like heart blockages or artery wall damage develop. However, most current computer models used to study blood flow treat arteries as if they are rigid and motionless
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explore how this programme could also work for children with SEN and complex needs, and engage parents and families more directly. Aim: To explore the impact of a school based PL programme for children with
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opportunities to be active. There are a number of PL programmes to support physical literacy and motor skills in children, however, the next step is to explore how this programme could also work for children with
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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