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Field
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research
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modelling using Finite Element (FE) method and FE simulation software (e.g. ANSYS), (3) Model Order Reduction (MOR) methods for mechanical simulation (4) numerical algorithms and models, and scientific
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group at King's College London led by Professor Bipin Rajendran. The group at King's is part of a consortium developing multiprocessor systems-on-chip with advanced nanoscale in-memory neural processing
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algorithms and models, and scientific computing programming (e.g. in MATLAB), and (5) modelling of material degradation and wear-out, reliability prediction models. Familiarity with failure modes of electronic
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, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer interaction, as well as participate in the full range of faculty responsibilities
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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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reducing odours from pomace and digestate. The project comprises seven work packages. As a leading partner, the University of Surrey will develop a system digital twin (SDT) to enhance overall sustainability