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explanations from machine learning models. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from
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-dependent source depletion. Reducing uncertainty in groundwater risk assessments through refined numerical methods. Applying the improved model to real-world groundwater contamination case studies. Career
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materials. Another major challenge is enabling motors to function in aqueous media, which opens up numerous opportunities for integrating motors with biological systems, i.e. to design responsive biohybrid
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of data-driven approaches within these multi-parameter models to produce faster and more robust correlations and tools that can be incorporated within industrial methods and have an impact on future designs
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equations, and numerical methods. Advanced programming skills in languages such as Python, C++, MATLAB, or R. Strong academic curiosity and enthusiasm for the chosen research area. Application Process To
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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will lead to natural collaboration opportunities. The primary methods used in this project will be experimental, involving fluid characterisation and high-speed imaging experiments, using Phantom high
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alarm signal or take other actions locally. We aim to implement methods for quality control and enhancement of data quality through approaches developed in other PhD projects within SFI Smart Ocean. These
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to describe a condition or make a decision to send an alarm signal or take other actions locally. We aim to implement methods for quality control and enhancement of data quality through approaches developed in
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, geomagnetism) and the development of corresponding numerical methods. We offer the opportunity to work in a small interdisciplinary research group consisting of mathematicians, computer (geo)scientists, and