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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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. This position seeks an experienced and recognized energy expert who can strategize and grow demand forecasting research at NLR. This is a recent example of one of the tools NLR has developed: https://tinyurl.com
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | about 24 hours ago
you will learn the specific methods you need for your project Feedback from experienced research advisers Excellent research facilities Instruction in English Thesis may be written in English or German
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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology
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» Computer engineering Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Positions Postdoc Positions Application Deadline 27 Feb 2026 - 17:00 (Europe/Athens) Country
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Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country France Application Deadline 13 Feb 2026 - 17:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Hours Per Week
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Georgia Tech prides itself on its technological resources, collaborations, high-quality student body, and its commitment to building an outstanding and diverse community of learning, discovery, and creation
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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, biofluids) data sources from primary or secondary sources. Applies a range of statistical, computational, and machine learning methods to research data. Provides guidance and training to junior analysts
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and