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Field
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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Reflectometry The aim of the PhD project is to provide machine learning (ML) based neutron reflectometry (NR) analysis as an automatized workflow for the reflectometry instruments at the Institut Laue-Langevin