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Are you interested to have an impact on how data-intensive experimental science is done?A fully funded 2-year postdoctoral positions is available in an interdisciplinary project at the departments of  and  at Aarhus University (AU). The position is part of a DFF grant that aims to develop machine learning methods for discerning and learning the constituent states of a fluctuating quantum material with high quality via Angle-Resolved Photoemission Spectroscopy (ARPES).The project aspires to carry on with a long tradition, in which experimental physics has relied on, and has often acted as a driving force for computer science to initiate research towards in complex analytical tasks via unsupervised ML, allowing for an understanding of measurements at simultaneously high spatial and temporal ...