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graduate entry requirements which include holding at least an upper second-class degree or equivalent qualifications in a relevant subject area such as mechanical engineering, physics, materials science, or
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, Environmental Sciences, or a closely related discipline. You will bring strong technical skills in building physics, dynamic thermal modelling, and environmental monitoring. Ideally, you will have experience with
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: An intelligent ATM is an ideal solution to analyse and monitor the local device for possible physical or cyber threats. A typical ATM system is suitable to host such environments. A typical system, consisting of
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process. Please quote reference NM46253 on your application and in any correspondence about this vacancy. The University actively supports equality, diversity and inclusion and encourages applications from
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, which are essential for safe operation in these challenging aerospace environments. You will develop robust, physics-based models to analyse failure, with a focus on understanding mechanical and
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mentorship for a prosperous post-PhD career. Who we are looking for: A first or upper-second-class degree in an appropriate discipline such as, materials science and engineering, physics, chemistry, nuclear
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process is poorly recorded and needs improvement. Aims and Objectives In collaboration with the Health Innovation Partnership, a modelling pipeline will be devised to cope with the challenges of data
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A PhD opportunity at the EPSRC Centre for Doctoral Training in Quantum Information Science and Technologies at the University of Sussex School of Mathematical & Physical Sciences The University
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to the application process. Please quote reference NM46253 on your application and in any correspondence about this vacancy. The University actively supports equality, diversity and inclusion and encourages
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical