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methods including machine learning methods to integrate genomics, transcriptomics and epigenomics data set to uncover genomic-epigenomic interactions and cancer evolution trajectories. The tasks will
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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Europe | about 1 month ago
, PortugalSupervisors: Dr. J. Pedro (INF), Prof. L. Cancela (Iscte)Apply here: https://match.iscte-iul.pt/phd-candidates-profiles/apply-to-dc-positions/Job information:Coordinator: Iscte – Instituto Universitário de
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candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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Job Code: 9521 - Research Assistant and 9529 - PhD Candidate Research Assistant Employee Class: Grad/Prof Student Position This position will provide support for lesson plan development relating
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning