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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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and apply cutting-edge methods in artificial intelligence (AI) to address urgent societal and environmental challenges such as improving food security, promoting animal welfare, protecting biodiversity
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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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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or related fields Expertise in advanced neurofunctional assessments and methods (e.g., computer vision, bioacoustics, machine learning/AI, neuroimaging, eye-tracking, multimodal data fusion) Excellent
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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