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Field
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augmentation, alongside conventional model evaluation. The role will also involve documenting methods and results for project deliverables, reports, and publications. The post is suited to candidates with either
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the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex. Only UK domiciled applicants who meet the following criteria may apply: Not already have a Master’s degree And Be
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the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex. Only UK domiciled applicants who meet the following criteria may apply: Not already have a master’s degree And Be
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diagnosis methods that combine analytical approaches based on drivetrain physical properties with AI-driven data analysis techniques to enhance the accuracy and effectiveness of fault detection and
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Responsible AI 39 Faculty of Computer Science Startdate: 15.10.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 12.10.2029 Reference no.: 6159
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scanning and measurement, garment fit evaluation, cloth simulation, digital twins, wearable sensing, smart textiles, and AI methods for clothing and body data analysis, to name a few. Applicants from
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This PhD project will investigate partial differential equations arising from kinetic models, with a particular focus on variational methods. The research will explore how variational structures
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the candidate completing 70 hours of teaching per year during the initial 3 years. The pan-University Graduate School offers an integrated training programme to the postgraduate community within a single centre
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, or evidence synthesis methods would be desirable, although training and support will be provided throughout the programme. Eligibility Criteria: A first-class or strong upper second-class (2:1) undergraduate
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of Sport, Exercise, and Nutrition Education – [email protected] This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: Athletes, coaches