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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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-year period and is funded by a Carlsberg Foundation Accomplish Grant to Prof. Nanna B. Karlsson. About the position This position is part of the research programme REGLA, investigating the physical
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for physical AI systems that learn and adapt through continuous exposure to multimodal sensory and radio data, and acts upon real-world environment through distributed coordination and control. Emphasis will be
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faculty determines the distribution of the various assignments. The weighting of the different assignments may vary over time. Employment as a postdoc requires scientific qualifications at PhD level at
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
Latin intellectual traditions. The project combines intellectual history with computational text analysis to examine large, historically complex corpora spanning multiple centuries and languages. The core
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systematic investigations of charge state distributions, fragmentation behavior under collisional- and electron-based dissociation, and differentiation of peptide isoforms and PTMs using negative ion mode
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Application Deadline 1 Jun 2026 - 12:00 (Europe/Copenhagen) Country Denmark Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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development through the Lecturer Training Programme and mentoring. An open and collaborative research culture within SDU’s Faculty of Engineering (TEK), promoting interdisciplinary innovation across electronics
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural