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increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result
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project. Computational mechanics PhD projects PhD 1: Rolling contact fatigue in green bearing steels – numerical microstructural modelling [SKF; Ron Peerlings] PhD 2: Predictive analysis of edge crack
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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modeling, construction of numerical methods, coding, testing, numerical simulations, and possibly measurements. You will mainly do your programming work in a mixed programming environment, i.e. combining
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interest in cell and developmental biology of plants; Experience in (numerical) mathematical modeling (e.g., vertex-based or Cellular Potts modeling, particle-based simulations, PDEs, FBA); Suitable
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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will be combined with theoretical modelling, statistical data analysis, and numerical simulations to identify the governing mechanisms and to determine whether and how proximity to a phase transition
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made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result, the model scale is doubling yearly, causing a proportional increase in the
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the structure and properties of the emerging scalar and vector potentials, establishing exact conditions and mathematical properties relevant to density-functional theory, performing numerically exact simulations
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, and how strain rate influences material behaviour. The resulting experimental data will be used to validate numerical models and contribute to certification by analysis of future composite structures