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-class expertise and supervision, customised training programmes, networking, outreach and career development opportunities, in addition to the standard training and development opportunities
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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of healthcare by examining the impact of bottom-up communities and networks promoting change. Healthcare accounts for approximately 5% of the UKs total carbon emissions, and significant activity is underway
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include contributing to the developing programme of work on decision analytic modelling in cancer research, develop networks and links with collaborators, external contacts and leading thinkers in
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networking with colleagues and students; planning and organising research resources and workshops. Successful applicants will have or be near to completing a PhD in computer science, information engineering
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isolation, leading to suboptimal network performance. This project seeks to address this gap by developing a holistic, system-level approach that optimises PST deployment strategies to enhance grid
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sleep patterns, gaining insights into sleep-related issues, and personalised sleep health management. However, the dynamic nature of sensor networks caused by frequently adding and removing nodes has
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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to International candidates. How to Apply All applications should be made online via the above ‘Apply’ button. Under ‘campus’ please select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we