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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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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
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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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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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endoscopists through a quantitative and qualitative assessment of the mucosal microstructure. You will be responsible for the algorithm development and implementation of the overall system. It is expected
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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project management, to co-ordinate multiple aspects of work to meet deadlines. The post will be based in the Department of Chemistry, Chemistry Research Laboratory, 12 Mansfield Road, Oxford, OX1 3TA and is