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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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atom-transfer radical polymerisation (SI-ATRP) and used to organise chromophores in 3D. You will develop solution-processing routes for the production of quantum optical materials, and design sensors
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-world systems. While most of the work will be computational or mathematical, you will also have the opportunity to visit BASF in Ludwigshafen, Germany for three months to try out the new algorithms in
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-edge research in machine learning and automated reasoning for safe algorithmic systems. The Research Fellow will be responsible for developing advanced theory and machine learning algorithms
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with UAVs for tackling wildfires, including modular, scalable methods with respect to the volume of collected data, to the number of UAVs, data sampling rates, number of sensors, centralised
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of such systems, but this is driven from the fundamental theoretical knowledge that underpin them. What you would be doing: You will be co-creating new models, algorithms and schemes to advance the field of joint
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development, planning and delivery of research funded by the UKRI MRC. You will also liaise with collaborators from Imperial College London on the design novel stimulators and sensors to use in the neonatal
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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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