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engineering, computer science applied to urban infrastructure, data science, or a related field. Expertise in numerical modeling and simulation for urban systems. Proficiency in digital twin tools and platforms
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with data-based models and numerical dynamo simulations. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events
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Qualifications PhD in the field of Planetary Science, Astronomy, Geoscience, or a related discipline by the start date of the position. Experience with numerical modeling and programming. Experience with modelling
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 4 hours ago
must be able to use a combination of numerical techniques and analytic perturbation theory to model more accurately the ringdown phase of black hole mergers, determining the non-linear contributions
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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
with numerical modeling (e.g., LES, DNS, or CFD) and/or laboratory experiments in stratified or rotating fluids. Ability to work both independently and collaboratively as part of an interdisciplinary
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green transition. About the project/work tasks: The overall goal of this PhD project is to develop methodologies for real-time modeling and inversion of geophysical well logs, with a particular focus on
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ecological benefits of large wood. Ecological Indicators 155, 111045. https://doi.org/10.1016/j.ecolind.2023.111045 Scolari, Fadul, Schwindt 2025. Hydro-morphodynamic numerical modeling indicates risk zones
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Research Associate position in the Department of Engineering, with a focus on undertaking both experimental and numerical studies within the hydrogen research hub (HI-ACT) funded by EPSRC. The project seeks
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: Experience with numerical modeling and/or data analytics with big data. Broad knowledge of hydrology. Experience in ML applications. Background Investigation Statement: Prior to hiring, the final candidate(s