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data analysis. The successful candidate will also be involved in the preparation of samples and their characterization using standard laboratory-based methods (optical and scanning electron microscopy
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skills in programming, modelling, and data analysis. Experience in formulating and solving mathematical optimization problems, as well as working on real-world demonstrators, is an asset. Proficiency in
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modeling tools (GEOS-Chem and CESM) and analysis of large observational datasets. The biosphere represents an important source of many reactive trace gases and aerosols (e.g. soil NOx, bioaerosols, BVOCs
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responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling, or generative modeling. Collaborating with
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supervision of Prof. Robin Erbacher, and is expected to play a leading role within the endcap muon CSC and/or GEM detector subsystems, both on upgrades and operations. They will also work on CMS data analysis