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Research theme: Chemometrics The project is jointly funded by the Community of Analytical Measurement Sciences and the University of Manchester Department of Chemistry. The successful candidate will
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. Comparison with known analytic methods and established Markov models will be made wherever possible. Expected outcomes include a unified non-Markovian framework for time series analysis, a suite of relevant
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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. Experience of advanced data analytics, including if possible experience of coding in Matlab and/or Python, is highly desirable. Experience of collecting neuroimaging and/or wearables data from infants/children
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project will involve collecting and analysing EEG, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab
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, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab and/or Python, is highly desirable. Experience
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UKHSA surveillance datasets to see if OTC sales can be used to monitor GI infection activity and better predict outbreaks. The PhD offers the unique opportunity to develop skills in analytical
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related discipline. You will have strong experience in one or more of the following areas: electrified powertrains, marine robotics systems, automation, or predictive maintenance using data analytics
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, data analytics, and co-designed interventions. This is an exciting opportunity to contribute to applied research that informs urban policy and planning, particularly around air quality monitoring and
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based