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Field
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, computing, and energy economics. The successful candidate will have an excellent understanding in one of the following fields: power system operations, power system economics, linear programming, micro
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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Project Description Explosive eruptions generate a range of types of rock types. Although studies typically focus on the vesicular (juvenile) material, the deposits also contain lithic fragments
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
based within the Manufacturing, Materials and Design theme at the Centre for Digital and Design Engineering (CDDE), which offers access to advanced simulation, visualisation, and high-performance
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a first-class or upper second-class degree (or equivalent) in Civil, Mechanical, Structural and Marine engineering or other relevant areas. Programme Package and Funding Our EnerHy PhD Studentship
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materials in lateral flow cassettes, covering aspects from engineering, manufacturing, economics and public perceptions. They will also develop the Diagnostic Discard exhibition to engage a broader public to
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testing and computational modelling. You'll become part of a diverse, multidisciplinary team that prioritises equity, diversity, and inclusion, gaining specialist expertise in hydrogen-material interactions
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computer science or mechanical engineering. The candidate will have programming experience, particularly on the development of machine learning pipelines. The University actively supports equality, diversity and
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will