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on regional-scale modeling and simulation of subsurface flow and geomechanics, including associated numerical and computational methods. Topics may include upscaling, numerical analysis, and the design and
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Master's degree in cybernetics, control systems, or equivalent, with a strong training in numerical optimization and optimal control. Additional training in machine learning and reinforcement learning is a
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systems, or equivalent, with a strong training in numerical optimization and optimal control. Additional training in machine learning and reinforcement learning is a plus. Your course of study must
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numerical modelling skills (e.g. Python, MATLAB, CFD codes) Personal characteristics Flexible and dependable Collaborative and independent Innovative and open minded Strong analytical skills Emphasis will be
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numerical modelling skills (e.g. Python, MATLAB, CFD codes) Personal characteristics Flexible and dependable Collaborative and independent Innovative and open minded Strong analytical skills Emphasis will be
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and innovative methods for predicting metocean data (primarily surface waves and ocean parameters such as currents, temperature, salinity, etc.) by combining advanced numerical simulations and deep
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section. The PhD-position's main objective is to qualify for work in research positions. You will report to the head of Department. Duties of the position Developing numerical models to simulate the thermo
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-intensive products composed of numerous parts, and is vulnerable to unexpected events. Smart technologies can collect, analyze, and represent data from various sources, significantly enhancing the visibility
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. The link between graphite crystallinity, flake size, and purity (all being important for industrial applications) and its formation history is not fully understood. Therefore, the numerous graphite
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of experimental studies and numerical simulations.Identification and assessment of safety related issues during in-situ handling of the biocarbon may be done through methods like inspections