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application: Experience with grey-box, hybrid, or reduced-order modeling techniques Familiarity with data-driven methods Experience collaborating in interdisciplinary research teams Background in chemical
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. This postdoctoral position at KTH focuses on developing advanced modelling frameworks and techno-economic analyses within two national research projects addressing virtual energy sharing and large-scale
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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and virtually. In doing so the traditional energy-supply business models will also evolve, as these plants will be able to stack additional revenues from their flexibility and capacity to perform sector
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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or more topics of focus of the evolved star group: 1) the extended atmospheres, 2) the wind-ISM interaction regions (including hydrodynamical modeling), 3) circumstellar magnetic fields, 4) circumstellar
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combines metabolomics, microbiome science and computational modelling to develop new food intake biomarkers and to understand individual metabolic responses to diet and develop personalized nutrition
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modelling in transdisciplinary processes in order to examine ecological and socio-spatial change, existing biodiversity governance regimes and develop multispecies ethnographies to better understand
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modeling of structural variability. The work may include inverse problems, regularization strategies, statistical modeling, representation learning, and geometric or variational approaches to volumetric data
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companies' transitions towards a sustainable society. In research and education, we work in a broad spectrum. From basic mechanical engineering via modelling and simulation towards innovative product-service