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background in Statistical Mechanics and to mostly focus on analytical work and the development of novel quantitative methods for active matter, and to a lesser extent, on computer simulations of active fluids
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reduction and uncertainty quantification for biological flows. The goal of the project is, in particular, the development of robust methods to quantify the propagation of domain uncertainties in
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methods to quantify the propagation of domain uncertainties in cardiovascular simulations, especially with regard to the estimation of biomarkers for image-based diagnostics. The project is a collaboration
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responsibilities: PIK is seeking a qualified junior researcher or postdoctoral scientist responsible for the estimation of future fire risk with the use of the updated SPITFIRE model, based on future projections of
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is seeking a qualified junior researcher or postdoctoral scientist responsible for the estimation of future fire risk with the use of the updated SPITFIRE model, based on future projections of
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methods to estimate the uncertainty in the daily predictions What do we expect from you? We seek a scientifically curious researcher who is passionate about understanding the environment. You should hold a
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bases and instruments in terms of their efficiency and incidence Applied game-theoretic modelling based on 1) and on numerical estimates of the benefits that potential donor countries derive from
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`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
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the team of Prof. Dr. Loriana Pelizzon on data and methods for supervision of climate and ESG risks in Capital Markets (incl. investment funds, bonds, stocks). The role involves advising and
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic