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approaches (e.g. SPG) as well as the use of machine learning, advanced computing, statistical modelling to explore the stochastic response to complex scenarios. This project offers the opportunity to undertake
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exploration to enable efficient mapping of unknown environments. Emphasis will be placed on leveraging SatCom connectivity and heterogeneous sensor data and real-time decision-making to adapt to complex
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the integrity of infrastructure such as pipelines and process plants. Traditional inspection and monitoring methods often face limitations when dealing with complex pipework and constrained geometries
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to analyse complex datasets, extract meaningful insights, and guide the optimisation of drug molecules. Collaborate with internal groups, including the Centre for Additive Manufacturing (CfAM) to design and
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to analyse complex datasets, extract meaningful insights, and guide the optimisation of drug molecules. Collaborate with internal groups, including the Centre for Additive Manufacturing (CfAM) to design and
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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introduced in workshop environments that handle many different materials, or during repair and maintenance work on complex systems where dissimilar materials are present. If materials to be joined
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Tandem Industry-Academy funded project https://www.vaikuttavuussaatio.fi/en/funded-projects/tandem-industry-academia-tia-seed-2024/ . developing next-generation optical computing technologies for ultra
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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government’s Advanced Modular Reactor (AMR) programme has recently identified HTGRs as the preferred design for future advanced nuclear deployment in the UK, with an aim to deliver a demonstration reactor by the