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framework to enable meta-analysis of multiple large biobank datasets, all of this with the aim of increasing our sensitivity to unravel the complex genetic causes of disease and, in so doing, identify new
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(Huybrechts), Global Analysis (Mueller), Topology (Barthel, Bottman, Ozornova, Ray, Schwede), Geometric Topology (Avramidi, Stadler), Representation Theory (Stroppel) and Mathematical Physics (Klemm, Blohmann
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Mathematical Sciences at the University of Göttingen as well as the associated research training groups "Fourier Analysis and Spectral Theory" and "Discovering structure in complex data: Statistics meets
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the aim of taking the complex spatial structure of clouds into account in climate models and global remote sensing. The position thus offers highly relevant and interesting opportunities for work and
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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to gain insights into complex systems and inform decision-making Design and evaluate scenarios that focus on energy systems and structural change, assessing their potential impact Develop and evaluate
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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or microfluidics and ideally in quantitative data analysis. As a theoretical candidate, you have knowledge in quantitative biology, soft matter/complex systems physics or statistical physics. You enjoy working in