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and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
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machine learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key
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Blavatnik School of Government ( https://ewada.ox.ac.uk ). It is essential that successful candidate would hold a relevant PhD/DPhil or being close to completion in computer science, machine learning, human
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in human-AI interaction to join a research team focussed on studying learning and decision-making in humans and machine learning systems. The Human Information Processing (HIP) Lab is headed by Prof
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We are seeking a full-time Postdoctoral Research Assistant to join the Machine Learning Research Group at the Department of Engineering Science (central Oxford). The post is funded by the Wellcome
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system planning, system modelling, multi-criteria decision analysis, data science, and machine learning. You will perform stakeholder engagement and on-the-ground data collection in LMIC contexts and
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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project and is fixed-term for two years, with the possibility of extension. The objective of this project is to carry out computer vision and machine learning research in order to be able to translate
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include: (1) creation of real-time indicators of digital connectivity by gender at granular spatial resolution using social media, population and survey datasets, and statistical and machine learning
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Dr Fabian Grabenhorst to play a key role in research on neurophysiology of learning and decision-making from nutrient rewards in animals (NHPs). The research is supported by the Wellcome Trust