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Flexible or Flawed? A Computational Neuroscience Approach to Learning Strategies and Psychiatric Traits
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ACCE+ DLA Programme: Uncovering the drivers of diversity in tropical savanna forests
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Magnetic Nanodevices for Energy-Efficient Neuromorphic Computing (S3.5-CMB-Hayward)
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AI-assisted grading of end-of-life wind turbine composite materials for a circular economy
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Numerical simulation of boiling flows for high heat flux fusion components (Associate University project at the University of Nottingham)
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-class or 2:1 MEng or and MSc with merit (over 60%) in a relevant area i.e. Chemical Engineering, Process Engineering, Chemistry, Materials Science, Geoscience etc. Candidates for socio-politico-economic
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Development and Validation of a Multimodal Wearable Headband for Objective Bruxism Monitoring Using Machine Learning (S3.5-DEN-Boissonade)
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First-class or 2:1 MEng or and MSc with merit (over 60%) in a relevant area i.e. Chemical Engineering, Process Engineering, Chemistry, Materials Science, Geoscience etc. Candidates for socio-politico
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candidates to have a First-class or 2:1 MEng or and MSc with merit (over 60%) in a relevant area i.e. Chemical Engineering, Process Engineering, Chemistry, Materials Science, Geoscience etc. Candidates
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engineering, material engineering or applied physics. The successful candidate will have: -Strong background in solid mechanics and engineering mathematics -Strong interests in computational work and laboratory