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problems in health data science. Air pollution is composed of several different environmental pollutants, for example particulate matter (PM10 and PM2.5), ozone (O3), nitrogen dioxide (NO2) and sulphur
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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effective delivery of expertise, equipment, and medical resources in response to complex and large-scale emergencies across the United Kingdom. In its initial phase, the research will examine past and
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the analysis of the complex data and cellular models (Big Data and Kavli Institutes). The DPhil will provide the student with multidisciplinary skills including specialized training in bioinformatics, genetic
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team of researchers using operational and information-theoretic tools to gain insights into quantum foundations, causality, and space-time physics. We are convinced that further progress on open problems
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researchers using operational and information-theoretic tools to gain insights into quantum foundations, causality, and space-time physics. We are convinced that further progress on open problems in physics is
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Fully funded positions available to start in 2025 or early 2026 Projects span plant genetics, climate-resilient breeding, AI and data science, soil health, sustainable agriculture, circular economy
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. The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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hole or neutron star orbiting at a large distance from a ‘normal’ companion star. This is a very long-lived state which accounts for the vast majority of the millions of binary systems harbouring neutron