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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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Engineering or related topic. Working experience and knowledge of nonlinear numerical modelling of structure and infrastructure exposed to multi-hazards conditions Working experience of advanced programming
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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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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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. Previous experience with data assimilation and numerical modeling will be regarded as positive in the selection process. Experience in automated processing of large data volumes. Experience with scientific
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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
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and perform numerical simulations To be successful at Level B please address the selection criteria A PhD or equivalent in data science, social network analysis, mathematical modelling, statistics
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-structures. Develop numerical algorithms and computer codes that can be used to model nonlinear optical effects pertaining to light-matter interaction. Validate the theoretical models and software tools by