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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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in cilia. Transport within cilia, the cell’s signalling and sensory antennae, is central to human biology. It enables these cell-surface organelles to assemble and dynamically change their proteome in
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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computational social choice, and aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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. The scope of the research will encompass aspects such as network monitoring, routing algorithms and network-hardware benchmarking. About you You should possess a MSc/MEng in Engineering, Computer
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods