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Field
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findings and stakeholder insights into accessible, evidence-based resources that support collaborative learning, knowledge exchange, and action. Document research outputs, including analysis and
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information or informal enquiries, please contact Dr Matthew Deakin, matthew.deakin@newcastle.ac.uk . The successful applicant may be eligible for a Global Talent Visa under the Endorsed Funder Route
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(AI) & Deep Reinforcement Learning (DRL) for energy optimization ✔ Predictive Maintenance & Failure Analysis using Machine Learning and Physics-Based Modelling ✔ Data Science & Advanced Analytics with
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-assisted design) and state-of-the-art experimental techniques (neutron scattering, data analysis, sample fabrication). The successful candidate will engage in cutting-edge research at the interface of theory
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transcriptomics and histone mark profiling as well as by live imaging approaches. As part of this project, you will have the opportunity to gain computational data analysis skills. This studentship comes with
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for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program
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production in the context of circular economy. The research activities in this doctoral thesis are planned with the view of developing a comprehensive multi-perspectives analysis approach, essential to track
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to the analysis of time series. In particular, the project 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
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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/College research strategy. 2. Document research output including analysis and interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate. 3