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. The successful candidate will have the opportunity to co-design the focus of this research project. Potential areas of research include integrating AI-enhanced weather forecasts with crop models, exploring tools
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University (principal supervisor Assoc. Prof. Claire Henry) and associate supervision will be provided by fellow academics in Screen or other discipline(s) as appropriate to the PhD project. The full-time PhD
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-year stipend scholarship to support pioneering research on wave energy converters. The successful candidate will work on cutting-edge experimental design and numerical modeling to better understand
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for ADHD emphasise core symptom clusters comprised of (1) inattention and (2) hyperactivity/impulsivity, various conceptual models of ADHD also highlight a prominent role for deficits in emotion regulation
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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nanoparticles in drug delivery or diagnostics, familiarity with cellular targeting, and use of computational tools to model nanoparticle behaviour. Experience in a regulated research environment is also
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mechanisms and transformer models. Qualifications Bachelor’s degree with First Class Honours (or equivalent) and/or a research master’s degree in computer science, AI or Computer Vision; or an equivalent
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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symptoms. Alexithymia is a major focus of our lab's research, whereby we have created new theoretical models of alexithymia (the attention-appraisal model of alexithymia; Preece et al., 2017), new