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should have: Demonstrated knowledge of fluid dynamics Experience with anisotropic viscous flow Experience with ice texture formation Skills in advanced computational methods. Knowledge of c++ program-ming
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techniques such as GMAW and laser-arc hybrid. The study shall be supported by numerical modelling and thermodynamic calculations. In the next step, the welds shall be characterized using advanced microscopy
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on theory, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
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group conduct research on concrete from material to structural level based on theoretical, numerical and experimental investigations. The Concrete group is involved in several national and international
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have expertise in at least one of the following research areas: PDEs, numerical methods, optimization, functional analysis, or stochastic analysis Candidates without a master’s degree have until 1st
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or competence in theoretical quantum physics and numerical simulations is a requirement. Experience with or competence with quantum computing and technology is an advantage. Experience from or competence in data
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in quantum chromodynamics. The work will involve a combination of theoretical modeling, numerical simulations of quantum dynamics, and the use of high-performance computing facilities. The candidate
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immediate leader will be associate Professor Victorien Prot. About the project This PhD position aims to increase our understanding of the mechanics of heart valve diseases using cutting-edge computational
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group conducts research on concrete from material to structural level based on theoretical, numerical and experimental investigations. The Concrete group is involved in several national and international