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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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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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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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involving protein structure prediction by AlphaFold 3 combined with crosslinking/mass-spectrometry and single particle cryogenic electron microscopy on native or recombinant TZ complexes, you are expected
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of predictive models for energy demand and production. These models will leverage techniques such as time series analysis and machine learning and will be integrated into a digital twin platform. The aim is to
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, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the immunological dysregulation inherent in T1D. Project Objective The PhD candidate will primarily focus on the clinical
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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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channels Predict variant-specific protein structures using AlphaFold Co-develop machine-learning approaches to incorporate quantum effects in molecular dynamics simulation Predict variant-specific drug
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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