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scientific discipline. • First-rate analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices/mechatronics •Ability to develop kinematic and
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comprehensive analysis of the extensive Pulse dataset, uncovering latent patterns and taxonomies that define building leakage characteristics. Surrogate Model Development: You will develop data-driven surrogate
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targets without compromising torque-speed performance. Aim This PhD project aims to develop a new generation of electric machines optimised for sustainability across the full lifecycle from material
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rely on unsustainable materials and on carbon-intensive manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next
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good partnership with the appropriate technical teams. Joint academic and industrial supervision. In this way, the student will develop both academic and industrial skills with multiple career
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appropriate technical teams. Joint academic and industrial supervision. In this way, the student will develop both academic and industrial skills with multiple career opportunities at the end of the PhD study
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fully funded, three-year PhD studentship starting in October 2025, focused on one of the following research objectives: To develop biomimetic designs that enhance energy harvesting and bioelectronic
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focus on robotic control. Building from some of the existing concepts on continual learning, the aim of this project will be to develop new frameworks for training and maintaining robustness and stability
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used to train surrogate models that can instantly predict quantities required by component scale CFD wall boiling models for different flow conditions and heat transfer surfaces. Key milestones
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materials research, to develop a wide range of skills in experimental and data analysis methodologies, and to be involved in end-to-end development and application of new, much-needed, additions to neutron