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of numerical methods for solving scattering problems and inverse problems (assessed at: application and interview) Proficiency in scientific programming languages, Julia or Python (assessed at: application and
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Computational modelling of the emergence of somatosensory cortical maps School of Psychology PhD Research Project Self Funded Dr Hannes Saal, Dr SP Wilson Application Deadline: Applications
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on a number of studies related to mesothelioma, including qualitative research exploring the support needs of family carers, a mixed methods study exploring factors influencing treatment access and a
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to translate this technology to clinical use. In this project we will ensure our supply chain, sterilisation and manufacturing methods can be performed to clinical standards at sufficient scale to progress
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flares using the assumption of hydrogen recombination continuum emission, in place of a blackbody estimate. In parallel, but not in collaboration, Pietrow, Cretegnier, Druett et al. (2024) have advanced
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or machine learning methods to tackle predictive questions. Proficiency in building and validating statistical methods and/or machine learning techniques in R or Python are also essential. Applicants
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explore data-driven methods including machine learning (ML) and artificial intelligence (AI) techniques, to develop predictive HMPM tools that can diagnose, detect, and predict faults in machinery
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Behaviours in Simulation: Develop methods to automatically generate diverse test scenarios in a virtual environment to efficiently find faults in robotic skills. This involves using intelligent techniques like
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research programme is to use genetic, molecular and cellular, and imaging/image analysis approaches to understand the development and function of the vertebrate inner ear, the organ of hearing and balance
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boron-containing heterocycles - cyclic compounds which contain one or more boron atoms. The aims of the project will be to develop chemical methods to prepare the new organoboron compounds, and explore