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Field
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projects, international collaborations, and experimental campaigns using software-defined radios and UAV operation platforms. The project offers mix of theoretical development, simulation-based research, and
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is an AI-based technique that supports imitation of the preferred system behaviour by using its behavioural history. It helps in the inference of the reward values by taking the observed history
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly
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. The project offers a rare mix of theoretical development, simulation-based research, and experimental validation, supported by advanced testbeds and datasets. Students will also be encouraged to present results
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overall efficiency. The project also involves building a real-time simulation environment, supporting the development of a hardware-in-the-loop (HiL) test bench, and validating the system through field
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scattering with computer modelling such as molecular dynamics simulations and AI-assisted data mining. The new technical capabilities will help bridge the current gap in biocide development, i.e., to link
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-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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to develop an SDT that simulates real-time system operation in a dynamic virtual environment. Online Implementation: Deploying the SDT on an evolving online platform, continuously updated with new data and