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to use your mathematical skills to model and design optical systems for sustainable high-tech devices for billions of people? Do you like to develop and analyze numerical methods for partial differential
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degree in mathematics or a related discipline Knowledge of solid mechanics, partial differential equations, asymptotic methods, numerical methods, and/or homogenisation are strongly desired Capacity and
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frequency domains; comfort with a wide range of numerical and analytical methods for electromagnetic characterization of lines and cables (characteristic matrices, FEM, MoM-SO, frequency-dependent earth
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 14 hours ago
experimental data collection programme in an experimental pipe rig and on numerical simulations. Duration: The research fellowship(s) will have the duration of 6 months. It’s expected to begin in February, 2026
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modeling strategies for multiphase flow systems. The PhD topic is on exploring how emerging quantum computing methods can be integrated with classical numerical models to improve the simulation of complex
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available in the Department of Physics at the University of Idaho. The primary focus of this position is advancing numerical relativity methods for compact binary systems. Specifically, the scholar will
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expertise in numerical modelling. The post is available from 1st March 2026 for 12 months in the first instance and could be extended further. See http://rccs.hw.ac.uk/ for more details. Key duties and
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Context Statement Position Overview A postdoctoral position is available in the Department of Physics at the University of Idaho. The primary focus of this position is advancing numerical relativity methods
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metadynamics methods. The numerical protocol will be set up on local machines, and data production will be carried out on national supercomputers (CINES, IDRIS). The results of the calculations will then be
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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory