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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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. Experience with isotopic box modeling, numerical simulations, and statistical analysis. Demonstration of effective communication of scientific and technical results (e.g., peer-reviewed publications
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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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collaboration with Lund University. The candidate is expected to have a strong mathematical background particularly in stochastic modeling, optimization, and reinforcement learning. As a PhD student, you devote
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the focus of this PhD project. The objectives of this work are to optimize an experimental setup for simultaneous tension/compression testing and localized corrosion measurements, including monitoring
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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 within interdisciplinary
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supervised by experts in combinatorial optimization, machine learning and fairness-awareness in algorithmic decision support, and the Eurotransplant headquarters in Leiden, where access to the domain expertise
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, as well as archaeometry (isotopic methods, bioarchaeology, histology). Numerous research projects are conducted at the Faculty of Archaeology, including those funded by external sources (NCN, ERC, COST
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methods to improve systems, and ML research develops such methods. Major gains are made when the development of ML and systems are symbiotic and co-optimized. This is relevant across a broad spectrum of
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work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g