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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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of image analysis in medicine Experience of programming in Matlab, software version control with Git, typesetting with LaTeX, use of Linux computers Experience with graph-based methods, and graph
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Lviv, Ukraine. The current research topics include disorder effects on phase transitions (diluted ferromagnets, long-range correlated defects, spin glasses, random graphs and networks), long-range
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Supervisors: Prof. Reinhard Maurer, Prof. Scott Habershon In drug discovery, millions of molecules need to be screened for their viability as drug candidate, including their synthetic viability
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). "Statistical field theory applied to complex networks” "Quantum geometrogenesis – Graph theoretic approaches to building spacetime” web page For further details or to discuss alternative project arrangements