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PhD in Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of
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addition to doctoral students, bridge fellowships for outstanding Master’s graduates and exploratory research grants for postdocs are regularly offered. All three groups of researchers form the interdisciplinary
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
by the Research Council of Norway and the partners for the period 2026-2030. There will be approximately 25 doctoral scholarships and some postdoc positions. Duties of the position Complete
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
oriented If you fulfill all the requirements, you may be eligible for a salary grade of up to E 13 50%. Social benefits are based on the Collective Wage Agreement for Public-Sector Employees (TVöD
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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Zukünftige Lebens- und Arbeitswelten. // We are looking for a full-time Postdoc (m/f/d) or Research Associate (m/f/d) to join our team immediately, initially on a fixed-term contract for 2 years, in the field
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since the primary language of the organisation is Danish, you should be prepared to learn Danish. Department of Hydrology You will be part of the Department of Hydrology. The department works with
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research school was launched in 2024 via the recruitment of 20 academic and 7 industrial PhD students. Over the course of the program, more than 260 doctoral students and 200 postdocs will be part of
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digital technologies. At HPI, you will benefit from close supervision by experienced professors and postdocs, cutting-edge research facilities, and a collaborative academic network, e.g. with the University
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking