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manufacturing processes for construction, including data-driven, sensing, and behaviour-informed robotic workflows. • AREA 3: Low-carbon 3D concrete printing, including computational design, process optimisation
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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31 Jan 2026 Job Information Organisation/Company Aalborg Universitet Department The Faculty of Engineering and Science, Department of Energy, Esbjerg Energy Section Research Field Engineering
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PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as Embedded AI, Edge AI, TinyML, and AIoT
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python
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to Spectro Inlets to help validate this device (Both DTU and Spectro Inlets are in the Copenhagen area). Thus there will be a high degree of technical analysis, benchmarking, and determining the capabilities
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content analysis, and a background in fields such as communication, the social sciences (e.g., sociology, psychology, political science), or data science. The candidate will work closely with Lena
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laboratories for testing: Oscillatory and capillary rheometers, Orthogonal rheometry (OSP), Dynamic mechanical analysis, micro/nano dynamic indenter, and AFM as well as a range of other instruments. What We
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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University, Denmark. Expected start date and duration of employment This is a 2–year position from 15 May 2026. Job description The work will be focused on analysis of faba bean interactions with rhizobia in