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studies of ices or materials. For PhD 3: experience or affinity with numerical modelling, fluid dynamics, or computational physics. Strong analytical skills and the ability to work independently and
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, architectural engineering, (applied) physics, applied mathematics, or a related field is required. Strong mathematical and analytical skills are essential. Solid understanding of numerical modeling and signal
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with spatiotemporal data analyses, remote sensing and numerical modelling; the ability to independently plan and organise the research, and to take a leading role in its direction; strong oral and
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numerical modelling and programming is an advantage; demonstrated ability to work both independently and collaboratively in an interdisciplinary and multicultural research environment; good organizational and
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use molecular modelling to simulate the milk fat globules and plant lipid droplets and guide the experimental work. Your qualities We are looking for a highly motivated candidate with a background in
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theoretical modeling, numerical simulation, and experimental validation. Key objectives can include: Developing theoretical and computational models for friction-induced damping in joints and interfaces
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research revolves around the following key objectives: Finding analytic expressions for families of numerical Hamiltonians that model magnetic topological semimetals. Classifying such Hamiltonians in terms
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postdoctoral researchers, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because
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van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model
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, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many