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software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
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Ability to lead and work in teams Essential Application/Interview Experience and capability in blast computational simulations using codes such as Viper:: Blast, machine learning, and/or LS Dyna Desirable
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» Autonomic computing Engineering » Maritime engineering Technology » Computer technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Apr 2026 - 23:59 (Europe
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
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Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
-world policy applications to equip students with the knowledge and tools needed to engage with AI at both strategic and operational levels. Students will learn how modern machine learning models work
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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, speaking); French is a plus but not mandatory. - Strong background in ecology. - Experience with statistical analysis using R; interest in machine learning is an asset. - Prior experience with one or more of
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how