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Field
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scales continues to be a fundamental area of research, particularly, considering the rapid changes humans induce. The development of numerical models together with the increased availability
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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and circular processes, enabling used products to be transformed into new generations. What you will do Design and implement core operations for Gaussian Mixture Models (GMMs), such as density
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of the model in Python • Parameterization based on real cell geometries and material properties • Numerical simulations of current and potential distribution for different stack designs • Comparative
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08.09.2025, Wissenschaftliches Personal with a strong connection to partial differential equations (numerics / analysis / modeling) (100%, TV-L) is available starting immediately. The position in
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and circular processes, enabling used products to be transformed into new generations. What you will do Design and implement a sampler for Gaussian Mixture Models (GMMs) Investigate and compare
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. Numerical models of varying complexity and different observational data sets are used to study atmospheric processes and phenomena on time scales ranging from single weather events to long term climate change
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of reaching climate neutrality by 2050. By leveraging characterisation, multiscale modelling, machine learning, and numerical optimisation, the project seeks to craft a magnetic multiscale modelling suite
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8,400 employees, including numerous top researchers, it is a globally renowned institution that is also of outstanding economic importance to the Rhine-Neckar metropolitan region. The following position
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of power system components for PowerDynamics.jl using the state of the art modeling language ModelingToolkit.jl (github.com/SciML/ModelingToolkit.jl) for high-performance symbolic-numeric computation in