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The successful candidate will be responsible for: 1. Develop the numerical and analytical tools required to design these tunable random architectures and predict the mechanical behavior
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methodological development and applied work, with expected contributions to scientific publications and participation in collaborative meetings with the partner institutions. PhD in AI or statistics, machine
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outsourcers. Data analysis basics (with Python or MatLab) is also demanded. General knowledge about embedded software programming may be required (but not compulsory).
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Hochschule München, jointly funded by the ANR and the DFG. Candidates should have a PhD in physics with good background in oxide materials, ferroelectrics or photoemission spectroscopy. The initial contract is