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, multimodal imaging, and AI-assisted diagnostics to enable safer and more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
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to have the following skills and experience: Essential criteria PhD (or near completion) in bioinformatics, computational biology, machine learning, or a related field Significant experience in the analysis
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. • Contribute to the development of appropriate programmes, modules and lectures in accordance with academic and military learning objectives. • Participate fully in assessment and examination processes as
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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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largest department in the IoPPN and focuses on the interface between psychiatry and medicine, psychiatry and occupation, psychiatry and the military, and psychiatry in different settings. About the role
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experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU