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phase of electronic neural networks is highly power-intensive, and their widespread use puts ever-increasing pressure on global energy infrastructure [1]. Photonic circuits guide and process light-based
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outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational capabilities (e.g. evidencing a 2:1 or higher in relevant
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, etc.), or the equivalent qualifications gained outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational
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outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational capabilities (e.g. evidencing a 2:1 or higher in relevant
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, addressing engineering questions in how future electricity networks can remain stable and resilient as renewable generation grows. Grid-forming (GFM) control is increasingly recognised as a critical enabling
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curiosity. This research project would ideally suit a candidate with a background in one of the following disciplines: Engineering, Physics, Optics, Computer Science, or Natural Sciences, although we are open
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regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven
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machine-learning-based surrogate models to accelerate design and control workflows. This PhD studentship would suit candidates with backgrounds or interests in engineering, physics, applied mathematics
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), Engineering and Physical Sciences Research Council (EPSRC) , and the Peter Sowerby Foundation ; in partnership with Health Data Research UK (HDR UK) and the Economic and Social Research Council’s
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operational efficiency and sustainability in remanufacturing contexts This funded PhD studentship is open to highly motivated candidates with a strong background in Engineering or a closely related discipline