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project establishes a scalable framework for automated atomic-scale image analysis that can be extended to more complex defect types, materials, and computational microscopy applications. Fellowship 2
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to experimentally characterise optomechanical frequency combs in the regimes of ‘self-pulsing’ and ‘phonon lasing’ in the MHz–GHz range. The aim is to characterise the device advantages and limits and to produce new
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, Matlab and/or R. Strong background in statistical analysis, applicable to experimental validation. Previous participation in scientific and/or technological research projects, preferably related to optics
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction