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, or a related field. Experience with numerical discretization methods for partial differential equations. Experience in computational modeling of geomechanical systems. Knowledge of continuum
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | 29 days ago
controllers be designed for systems represented by learned operators? You will combine analytical theory with numerical implementation and validate the developed methods on industrially relevant
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | about 2 months ago
? No Offer Description Are you fascinated by application-oriented research in mathematics and eager to work at the interface of numerical optimization, optical design, and uncertainty quantification
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Scholar in physical oceanography focused on numerical ocean modeling, ocean data assimilation, and computational methods for understanding and predicting regional and coastal ocean circulation. This is
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 13 hours ago
) for a collaborative project with a starting date of April 1, 2020. The candidate will be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and
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activity will focus on the development and application of numerical methods for thermal-hydraulic analysis at both the system and component levels. The work will involve analyzing operating, transient
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at King’s on quantum algorithms and numerical methods for many-body dynamics beyond the reach of standard classical simulation. About the role We have a high preference for a candidates who is willing
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approach our aims, we develop our own numerical methods and tools, but also extensively employ and co-develop numerical techniques provided by the international community. We are looking for one PhD
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cyclones, the Madden–Julian Oscillation, and atmospheric rivers. We combine theory, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics
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thermodynamic and kinetic models into an alloy design framework (including material properties models) that uses numerical optimization methods to rapidly screen for promising compositions over vast multi