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University of Oslo and UiT The Arctic University of Norway | Norway, Michigan | United States | about 21 hours ago
/61927781301 Application and more information: https://www.jobbnorge.no/en/available-jobs/job/303593/phd-fellowships-in-knowledge-driven-machine-learning-in-norway-8-positions Keywords: Bayesian
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professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ Your work assignments Machine learning, and in particular deep learning, requires
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requirements of Monash for PhD (https://www.monash.edu/graduate-research/future-students/apply); Knowledge of machine learning (would be a plus if familiar with NLP and Medical AI); Knowledge of cybersecurity
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-supervised machine learning methods for biological data where reliable labels are scarce, expensive, or impossible to obtain. The aim is to train models on synthetic data generated by biophysical
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quantum attacks Verifiable and privacy-preserving machine learning (e.g. proving model integrity or fairness without revealing training data) Scalable ZK-proof constructions for federated and
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Informatics ( DBMI ) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a
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PhD student focusing on Machine Learning of Geometric Representations at ISY Linkoping Reference number LiU-2026-03853 We have the power of over 50,000 students and co-workers. Students who provide
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Primary supervisor Levin Kuhlmann Research area Machine Learning What makes a machine conscious? This PhD would be at the intersection of Philosophy, AI and neuroscience. You would study the latest
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Primary supervisor Levin Kuhlmann Research area Machine Learning What makes a machine conscious? This PhD would be at the intersection of Philosophy, AI and neuroscience. You would study the latest
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PhD in Materials Science Norrkoping Reference number LiU-2026-03852 Join us in developing machine-learning accelerated simulation methods to understand and optimize interfaces in hybrid organic