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equivalencies: https://hr.uky.edu/employment/working-uk/equivalencies Required Related Experience 4 yrs Required License/Registration/Certification None Physical Requirements This position requires regularly
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 5 days ago
Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of AI4Quantum – Machine Learning for Quantum Simulation and Computing is looking for a PhD
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to translational R&D project coordination at the interface between biotech and academia. Visit the link to access full mandatory requirements: https://drive.google.com/file/d/1XDXQtA4qDGWvBw1YR5lQt2APng3oCE7y/view
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programming, including public art learning tours and activities, family day programs, artist talks, and other events. Organizes administrative tasks related to K-12 and family programs including coordination
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will be considered). • Teaching Experience: Demonstrated experience teaching undergraduate courses, including core data science topics such as statistics, data visualization, and machine learning
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family: Paid Time Off – Generous vacation, holiday, sick, and military leave Retirement Contributions – Purdue contributes up to 8% of your annual income Educational Opportunities – Tuition assistance
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16 Jan 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Educational sciences » Education Educational sciences » Learning studies Engineering
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knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data