37 postdoc-distributed-algorithms Postdoctoral research jobs at University of Oxford in United Kingdom
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide an exceptional launchpad
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to less experienced members of the research group, including postdocs, research assistants, technicians, and PhD and project students. In this post you will manage your own academic research and
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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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development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide an exceptional
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incorporated into cellular function. We are now looking for a postdoc with expertise in IDPs and NMR that can help us study these systems in more detail. Training will be provided in NMR, programming methods
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2022, PMID: 36462505). The research will be conducted in a friendly and supportive atmosphere with access to outstanding facilities and within a vibrant postdoc community. The applicant should hold, or
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incorporated into cellular function. We are now looking for a postdoc to study the physicochemical properties of membraneless organelles and the links to neurodegenerative disease. The candidate will have
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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