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of biomechanical analysis into a new era. Considering the size of the pitch along with the stochastic nature of football there are questions relating to the accuracy of this kinematic data, which forms the basis
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for biological sample preparation prior to analysis, development and validation of separation methods for use in pharmaceutical analysis and bioanalysis, interpretation of the data obtained in relation
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research in the broad field of computational methods for the built environment. Particular emphasis is placed on building information modelling, digital drawings, point cloud capturing and processing as
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Application deadline: All year round Research theme: Numerical Analysis This 3.5 year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply
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), machine learning (ML), deep learning (DL) and Data science methods for medical image analysis, to autonomously grade the fundus images from large datasets. This will be supported by Professor Neil Vaughan
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analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g., GraphPad Prism, R, or Python
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, and/or data analysis, to address topics related to one of: Understanding depth-related plasticity in the physiology and behaviour of mesophotic reef fish. Identifying depth-related changes in
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-cell imaging) or image analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g
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for experiments using reinforcement learning, Bayesian methods, image analysis and data analysis. Collaborate with interdisciplinary teams, including machine learning experts, device modelling specialist
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an international supervisory team. Depending on your current and desired skills and interests, your PhD will combine fieldwork, lab-work, and/or data analysis, to address topics related to one of: Understanding