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opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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, b) computational modelling, or c) machine learning. This is a complex project managing longitudinal data from a range of sources. Therefore, thoroughness and attention to detail while managing
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu For questions, please email mweber@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential