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-holomorphic Hilbert Modular Forms”. The central aim of the project is to develop explicit algorithms for computing with non-holomorphic Hilbert Modular Forms and using these algorithms together with theoretical
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platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions for distribution electric
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10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
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that can maximise yields, whilst controlling morphology and particle size distributions. These MOFs are being used for carbon capture and, more broadly, this project relates to global warming. Sustainable
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challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
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times. You will act as the primary point of contact for Senior Department Managers responding efficiently and effectively to internal and external queries and will process and distribute orders via
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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throughout the academic year; communicating details of meetings to relevant staff; production and distribution of minutes/notes of meetings; literature searches, assisting in the facilitation of large grant
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precision Mechatronics systems and algorithms. Ability to develop kinematic and/or dynamic analysis of Mechanical/Robotic systems. Ability to implement control and kinematics with hardware-in-the–loop
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-or-leave decisions, but how we make them is not well understood. The goal of this project is to find out if there is common decision algorithm for leaving across species and what that algorithm is. You will