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Multiple Sclerosis (MS) with a view to highlighting the implications for clinical practice. A recently completed PhD (PhD1) study, supervised by Dr Andrea Hollomotz and Professor Helen Ford at the University
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, aligning with the Medicine without Doctors wider vision and combining methodological approaches from medical sociology, medical anthropology, STS, and history, to study the emergence and standardisation
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services research and epidemiology, along with practical skills in managing large, complex datasets. Proficiency in statistical software, especially STATA, is essential. You must be able to handle multiple
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Abuse (DVA) experiences of people with Multiple Sclerosis (MS) with a view to highlighting the implications for clinical practice. A recently completed PhD (PhD1) study, supervised by Dr Andrea Hollomotz
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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and modelling of African malaria vectors and malaria transmission F2 Experience working with multiple partners either in academia or in malaria endemic countries F3 An emerging national or international
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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, developing solutions for removing and storing greenhouse gases into the built environment, and developing the life cycle assessment method for quantifying multiple cycles of using building products. Your role
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research aligned with the Materials, Concepts and Reaction Engineering Group [1]. As this position will be funded by a specific research grant [2], you must have experience in laboratory experiments with ion
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural