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of Chemistry, and the group of Prof. Hobolth at the Department of Mathematics. A second postdoc with expertise in stochastic processes and statistical methods will be part of the project and you are expected
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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protein engineering, characterization of protein interactions by various methods, de novo design of protein binders, integrative structural biology using NMR, SAXS and/or single molecule FRET. Your profile
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otolith-based method and relate FMR to oceanographic and ecological conditions along north-south and fjord-offshore gradients in East Greenland. Experience with isotope analyses and arctic field work
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SGS modeling) and RANS. This includes proposals of new methodologies, implementation and validation of the methods using the simulation and experimental data, reporting of the results, and dissemination
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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The candidate will be part of the MUNI-RISK and MMinE-SwEEPER consortia that will advance scientific understanding on risks of munition in the marine environment and develop methods for risk prioritizing and