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Field
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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workflow for the imaging of Mg-LPSO alloys via X-ray nanotomography followed by higher resolution imaging of the identified regions of interest using transmission electron microscopy and atom probe
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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spectroscopic and imaging methods for the contactless detection of plant conditions. The position is being advertised as part of the joint project ‘LaserRoots: A new way for the sustainable production of climate
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imaging with image analysis, and spatial genomics and proteomics. The position will be responsible for participation in seminars, professional development opportunities, manuscript preparation and
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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, understand its role in therapy resistance, and identify novel regulators using innovative CRISPR screening approaches combined with advanced imaging, single-cell transcriptomics, and phospho-proteomics.
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student, you will be embedded in the research groups Computational Imaging and Deep Learning (CIDL) and Applied Quantum Algorithms (aQa), part of the Leiden Institute of Advanced Computer Science (LIACS
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Graduate School at the Center for the Theory and History of the Image at the University of Basel invites applications for two positions for doctoral study on the theory and history of the image for four