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three main phases. In the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam
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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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, preferably with a proven background in, or willingness to learn, physics-based numerical modelling and programming skills, in Python (preferably), R, MATLAB, or a comparable language. Openness to collaborate
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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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analytical skills, a strong interest in numerical modeling, and good programming skills in Python is required. Eligibility criteria Fulfillment of eligibility criteria is dictated by the European Commission
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interest in numerical modeling, and good programming skills in Python is required. Eligibility criteria Fulfillment of eligibility criteria is dictated by the European Commission under the Horizon MSCA
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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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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, a key component of natural gas and a by-product of numerous industrial processes such as naphtha cracking, presents a compelling opportunity. Current practices, such as combusting methane to sustain
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essential for transitioning to a carbon-neutral and energy-efficient society. Methane, a key component of natural gas and a by-product of numerous industrial processes such as naphtha cracking, presents a