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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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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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in a collaborative research environment. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical university globally recognized for the excellence
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histories in Central Eurasia by applying palaeoproteomic methods to a selected number of archaeological sites in the region. The position is based in a research group composed of evolutionary and molecular
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afterwards. The position is part of the DFF Sapere Aude project MiddleEarth, which aims provide unique insights into the hominin occupation histories in Central Eurasia by applying palaeoproteomic methods to a
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model systems for electrocatalysis Surface characterization using near-ambient pressure XPS (NAP-XPS) Method development for electrocatalysis measurements Scanning probe microscopy Synchrotron beam times
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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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to contribute to the supervision and training of BSc, MSc, and PhD students, as well as to teaching and outreach activities within the department. As a formal qualification, you must hold a PhD degree (or
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. As a formal qualification, you must hold a PhD degree (or equivalent). General qualifications Strong scientific track record and research potential at the international level Ability to work
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to quantify the uncertainty in model outputs using different methods. Run scenario analysis to identify management practices with the largest mitigation potential, both spatially and temporally Support training