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applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be inherently dangerous demanding very precise assembly tasks, and so flexible automation
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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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of disease dynamics that will be used to assess the potential impact of novel treatments on controlling the transmission of emerging respiratory infections in highly heterogeneous populations. As part of
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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(3.5 years). Project Description Background and context: Optogenetics is a powerful and controlled neuromodulation technique, which mostly used to study the brain by using neural implant containing light
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project will develop novel methods for modelling and controlling large gossamer satellites (LGSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. The candidate will
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electronic converters are required to connect renewable energy sources and energy storage systems to the power network. These converters employ sophisticated control algorithms that must simultaneously achieve
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: Understanding and Targeting Cell Cycle Control in Cancer BRIEF DESCRIPTION OF THE PROJECT: Cells must duplicate their DNA, grow, and repair DNA damage before committing to mitosis — a critical decision point that
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Electrical Capacitance Tomography (ECT) to study the combustion processes of hybrid propellant propulsion systems. To perform inflight tests using the ECT as hardware in the loop to control O/F ratios in a
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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