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: · Learning how to express software requirements precisely using formal models. · Using these specifications to automatically generate test cases for software systems and code. · Exploring how test
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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
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work. The project will involve: Learning how to express software requirements precisely using formal models. Using these specifications to automatically generate test cases for software systems and code
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: (a) security, (b) reliability, (c) selectivity, (d) speed, and (e) robustness. https://www.spenergynetworks.co.uk/pages/d_suite_project.aspx Number Of Awards 1 Start Date October 2026 Award Duration 4
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to working prototype to deployable product. What you'll gain: Hands-on privacy engineering experience in an industrial R&D environment Access to Keepl's platform, case studies, and engineering mentorship
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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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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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under uncertainty (Studentship code MSP106) Learning to sample: Meta-optimisation of gradient flows using reinforcement learning (Studentship code MSP107) Dynamic Bayesian modelling of endurance sports
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8090F select ‘‘PhD Mechanical Engineering (full time) - 8090' as the programme of study You will then
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: search for the ‘Course Title’ using the programme code: 8040F select ‘Civil Engineering PhD (full time) – 8040F' as the programme of study You will then need to provide the following information in