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Field
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organisational skills and the ability to research, problem-solve, design, and implement ideas in a fast-paced, hands-on environment. In this role, you will be required to have a practical approach, a positive
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analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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This 3-year PhD position offers an exciting opportunity to join the STRIPS Project (Swansea Tata Research and Innovation Prosperity Partnership for Printed Perovskite PV). As part of the STRIPS
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) change tread pattern (or tread groove depth), ii) aerodynamics by changing the surface texture of sidewall, iii) noise cancelling (vibration), iv) mechanical properties (hardness). Resources: The PhD
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turbulence, and use this knowledge to identify control strategies through deep reinforcement learning. The methods developed in this project will directly contribute to designing novel porous media
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awareness capabilities. The PhD will involve both simulation and experimental work. This includes designing and testing optical instrumentation and conducting observation campaigns to image and track
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requires not only quantification of respective changes in materials but also development of novel tools for design and optimisation of new engineering solutions. This will be achieved by combining
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) for different scientific applications, including simulations, large-scale data analyses and AI. This will involve designing test protocols, building test benches to track power and energy usage, and running
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student with project development, site selection, data collection and GIS mapping. Suggested timeline: 1 week project design and development, 2 weeks GIS mapping, 1 week fieldwork, 2 weeks collate and