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Field
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/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
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on healthcare data. - Experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record
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about applying deep learning to decode the regulatory grammar of plant genomes and translating predictions into testable biological hypotheses, we invite you to join the Omics Data Analysis and
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monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
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At AAU Energy, a position as Postdoc in AI and Deep Learning for Radar-Based Non-Destructive Testing is open for appointment from 01.10.2026 or as soon as possible hereafter. The position is
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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scattering and direct dark matter detection, using advanced cryogenic detectors. The MBI hosts a research group dedicated to Machine Learning in Particle Physics. Qualifications: PhD in Particle Physics
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origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including