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) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware
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reliable decision-making. Evolutionary algorithms will be employed to efficiently explore the parameter space and undertake sensitivity analyses. The integrated framework will be validated using analytical
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will also work closely with our industrial partner on process engineering for a scalable prototype facility and product output testing. The successful PhD student will be supervised by Prof Anh Phan from
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Duration 4 years Application Closing Date 16th January 2026 Sponsor EPSRC Supervisors Dr Leo Tsui , Prof Noel Healy Eligibility Criteria We are adopting a contextual admissions process. This means we will
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prototype facility and product output testing. The successful PhD student will be supervised by Prof Anh Phan from the Process Intensification Group at Newcastle University. There will also be an industrial
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enable next generation photonic devices for quantum applications. Number of awards: 1 Start date: 1st October 2026 Award duration: 4 years Sponsor: EPSRC Supervisors: Dr Leo Tsui , Prof Noel Healy
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(NERC) Supervisors Prof Bethan Davies , Newcastle University Eligibility Criteria You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a subject relevant to the
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. Number Of Awards: 1 Start Date: 1st October 2026 Award Duration: 3.5 years Application Closing Date: 8th January 2026 Sponsor: Natural Environment Research Council Supervisors: Prof Hayley Fowler
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in