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and data-based models for describing complex materials and (re)active molecules with a focus on their interfaces. Development and implementation of new methodologies and algorithms for simulating
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in the network. Here unfair indicates that people with different personal traits are differently and unjustly affected by algorithms not designed to consider those traits. This project aims to develop
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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates
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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments
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the Department of Information Technology website . At the Division of Systems and Control , we develop and analyze both theory and concrete tools to design systems that learn, reason, and act in