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Field
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analysis and application of machine learning techniques to structured numerical and unstructured textual data; (d) have a good track record of academic writing, including report writing, manuscript
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derived theoretical frameworks from the European Research Council – Starting grant ‘OceanCoupling ’ project and numerically implement the theoretical models. Interested applicants must address why and how
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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-shear rheometry. Bridge Theory and Practice: Develop and validate cutting-edge theoretical and numerical models connecting suspension mechanics to gravity separation performance. Collaborate and Impact
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recirculating flumes, velocity measurement systems, spectroscopic tools, and numerical modeling platforms, to investigate hydrologic and sediment processes. Works closely with USGS scientists and University
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++, or Julia, with strong numerical modeling, data analysis, and reproducible code development skills; experience with Git-based workflows and AI or ML for science is a plus. Experience designing and executing
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signal processing, imaging, inversion, or source characterization, is highly desirable. Proficiency in Python, C++, or Julia, with strong numerical modeling, data analysis, and reproducible code
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Python, C++, or Julia, with strong signal processing, numerical modeling, and data analysis skills; experience with Git-based workflows and AI/ML for science is a plus. Hands-on experience in structural
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-on experience in motor development Familiar with electric motor design and development Knowledge in analytical and numerical modelling Publication track record is an advantage We regret to inform that only
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Institute of Sound and Vibration Research, University of Southampton, drawing on expertise in aeroacoustics, acoustic liners, metamaterials, numerical modelling and experimental testing. The project includes