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(or equivalent) for appointment at Research Associate level and have previous experience in research and innovation in IBRs and power systems. You should have deep knowledge on load modelling, as well as power
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new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad
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and resistance, and single cell RNA sequencing to characterise the resistant phenotype Apply mathematical frameworks to learn the dynamics of resistance evolution Combine experimental results with
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a working, learning and social environment in which the rights and dignity of all its staff and students and stakeholders are respected. We recognise the broad range of experiences that a diverse
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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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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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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teach you many translatable skills and knowledge from the fields of sleep medicine, sleep physiology, statistics, artificial intelligence, and psychology for example. A very significant and specific
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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