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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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Learning Contexts TLTED 5005 - Equity, Diversity, and Justice in Education TLTED 5108 - Teaching and Learning of Mathematics in Grades Pre-K - 5 MATH 1050 - Precollege Mathematics I MATH 1075 - Precollege
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Professor will be responsible for teaching undergraduate and graduate courses in computer systems and algorithm design on a temporary basis. Teaching may be in our core courses alongside other faculty
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(specializing in Strategic Management: https://strategy.univie.ac.at/phd/ ) envisaged starting date: 15 June 2026 (for a total duration of 4 years; Initially limited to 1.5 years, the employment relationship is
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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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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 10 days ago
acquisition Good communication skills in English and ability to collaborate in interdisciplinary teams Desirable qualifications Experience with machine learning methods for regression or signal interpretation
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to take part in the supervision of PhD students and the teaching activities of the research group. Your network and team Currently, our research group consists of 1 professor, 1 lecturer, 1 staff scientist
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measurement technique development, atmospheric modelling, and advanced methods for integrating observational and model data through data assimilation and machine learning. About the research project The overall
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the department and teach courses if they choose to do so. Education and Experience: Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in
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supervise PhD students. The rest of your time (40%) is devoted to teaching. The department has developed several courses within data science, e.g., Bayesian methods, Advanced Machine Learning, Deep Learning