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be used to prepare lamella samples for high resolution cryo-EM imaging and tomography. From AI assisted image analysis, 3D models for key proteins and biomolecular complexes will be fitted into 3D
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and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
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combining CRISPR-based endogenous protein tagging, advanced quantitative imaging, and biochemical approaches, this project seeks to uncover novel principles of replisome plasticity. A key long-term objective
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information on working in Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your complete online application must be submitted no later than 24 March 2026 (23:59 Danish time). Applications
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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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hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project
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to prototype validation and measurement activities. Document design choices, trade-offs, and experimental results in high-quality publications. The position offers the opportunity to establish an independent
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Arbøll, e-mail: tpa@hum.ku.dk . Application Submit the application online in Adobe PDF or Word format. Please click on the “Apply now” icon at the bottom of this page. The application must be written in