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knowledge. This project requires specific and essential skills; however, these can be learnt throughout the PhD and with help from supervisory team. These may include: · Difficulties with learning how
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theory, Bayesian inference, Monte Carlo simulation, and statistical analysis of subjective data. Data science and machine learning - big data analytics, surrogate modelling, digital twin development, and
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Biotech Campus (Sand Hutton), with short visits to Newcastle for training and technology transfer. Fera Science Ltd is a world-leading analytical laboratory with a strong track record in developing and
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technology transfer. Fera Science Ltd is a world-leading analytical laboratory with a strong track record in developing and deploying cutting-edge diagnostic technologies, including qPCR, LAMP, and high
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EPSRC ReNU+ CDT PhD Studentship: Physics-informed machine learning for deep geothermal systems under uncertainty. Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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equations to simulate pollutant transport, mixing and biochemical processes. To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained
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: · Learning how to express software requirements precisely using formal models. · Using these specifications to automatically generate test cases for software systems and code. · Exploring how test
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks