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. Nature Physics20, 970 (2024)). You will also work on expanding our coherent imaging methodology to look at dynamics and phase switching in materials at the nanoscale (Johnson et al. Nature Physics19, 215
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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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, load modelling, soil–structure interaction, and relevant degradation and failure mechanisms over extended service periods. Within the scope of the project, a small-scale prototype will be tested in AAU
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. If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your complete online application must be submitted
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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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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your complete online application must be submitted no later than 12 February 2026 (23:59 Danish time). Applications must be submitted as
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, cellular biophysics or optical instrumentation. Responsibilities and qualifications We imagine that one of our new colleagues has experience in construction and/or operation of home-built optical setups
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structure quantification by tomography and imaging Perform testing across different scales, i.e. characterizing the viscoelastic properties of the base material and the nonlinear mechanics of the scaffolds
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
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