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on astrophysical source populations and dark-matter signals, exploiting statistical correlations across datasets to break degeneracies that limit single-probe analyses. The framework will be validated on synthetic
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school, and taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a
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superconductivity, quantum materials, Josephson electronics, open quantum systems, flat-band physics and momentum space topology. The group currently consists of three senior researchers, seven postdocs and four PhD
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