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. Being able to predictively design particle properties is of great economic value and is applicable to a range of industries such as pharmaceuticals, agrochemical, additives, cosmetics and food
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Robotics, Embedded Systems, Medical Sensors, Sensor Design
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-molecular interactions will provide a wealth of new inforamtion, which can be used to improve predictive design and control of crystallisation using machine-learning methods. This studentship will entail
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the development and application of digital process modelling tools to investigate the influence of reactor design and processing conditions on the crystal properties. In this project, precipitation process models
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sludge rheology, it will be possible to design processes that can handle variable waste streams and produce encapsulated wastes that are safe for long term storage. The project will contribute to the clean
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, this project with apply the result to further train neural network-based machine learning models, with the aim of developing predictive tools for the rational design of future materials. Please state your entry
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on agitated tubular reactors. The project will investigate new mechanical designs for exchange units, as well as characterise the liquid fluid dynamics and develop new ion exchange materials, based on 3D
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patient-specific implant designs. You will aim to develop a combination of in silico and in vitro models of wrist repair that can assess the risk of tissue damage following surgery. The PhD project will
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of photonic qubits is the capability to generate large numbers of single photons with identical quantum properties. Increasing the level of indistinguishability of single photons optically requires designing
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to minutes per ligands. The most successful ligands identified in silico will be prepared and validated experimentally. Further refinement of the lead ligands through rational design, computational evaluation