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to the quantum level. In the focus are advanced techniques for the preparation of controlled atomic, molecular and cluster ensembles, combined with modern ultra-short laser techniques, as well as a variety of
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computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably
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understanding of the key factors that affect their performance is limited by the fact that most of the characterisation techniques used in the field obtain average properties of what in reality is an ensemble
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to describe ocean turbulent fluxes #developing theoretical and conceptual models to understand and predict ocean mixing #work as an integrative part of a motivated multidisciplinary team within the institute
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PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
important part of our personnel policy. Your tasks #analysis and bias adjustment of an existing large ensemble of regional climate model simulations for Hamburg and Heide #development of impactful heatwave
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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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to gain insights into the genetic underpinnings of disease and improve genetic risk prediction. We seek to build on previous expertise and methods devised by our teams (see below), including incorporating
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highly accurate computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW
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though dryland soils have low organic carbon (OC) concentrations, they store a significant fraction of global soil OC stocks. However, predicting effects of increasing aridity on soil OC stocks is not yet