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prior exposure to modern developments in biomathematics and will also have a solid knowledge of mathematical analysis, partial differential equations as well as kinetic theory and will be able to take
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the network architecture need to be to capture the solution accurately? In essence, we’re exploring the frontier between modern machine learning and classical mathematical theory—where neural networks meet some
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administration The research should focus on data mining, e.g., clustering, representation learning, causality detection and graph mining. This is part of your personality: Master in Computer Science, Applied
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flows such as entropy dissipation. This is a chance to tackle cutting-edge mathematical and computational problems with real-world relevance, using modern approximation theory and machine learning
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with graph learning, in particular using graph neural networks (evidenced by publications in top-tier journals or conference proceedings). Excellent and up-to-date knowledge of typical machine learning
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group “Foundations of Cryptography” within the research group “Theory and Applications of Algorithms” at the department of Computer Science focuses on provable security of cryptographic schemes. We
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) Mathematics, or a related discipline (Statistics, Econometrics) Knowledge in analytical research methods, such as game theory, information economics, or microeconomics Excellent command of written and spoken
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Cleanroom Technologist – Research Group Katsaros
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Laboratory Manager & Research Technician with focus on optical investigations of quantum materials – Sunko group
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Laboratory Management & Research Technician– Kicheva group