68 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" uni jobs at Technical University of Denmark in Denmark
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materials, utilizing hyperspectral imaging data as input. We want to enable real-time prediction and assessment of the materials’ physicochemical behaviour and performance characteristics. This position is
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technology and characterisation. Background within image processing, computer vision, or related fields. Background within in-line process monitoring or related fields. Furthermore, it is an additional
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on the economic impacts of renewable energy based on econometric methods. The work to be undertaken is related to a project, which will draw on input-output models that are tailored to sub-national level data in
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additional information about the position, please contact Associate Professor and Head of Research Group, Mohammadamin Mohammadifar on moamo@food.dtu.dk Applications received after the deadline will not be
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, thermodynamic models, and unit operations, developed as part of research projects at both CERE and KTC. These software tools include but are not limited to the Integrated Computer Aided System (ICAS), CAPCO2
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attach your motivated application, CV and exam certificates. If you would like additional information about the position, please contact Team Lead Innovation Partners, Mette Blaabjerg on 2748 4444
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-event data collection + feedback Assist with analyses and PowerPoint for ongoing projects. Support partner recruitment in our scaling phase (e.g., prospect research) SoMe knowledge is a plus but not a
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certificates. If you would like additional information about the position, please contact Jörg Hübner, Director, jhub@dtu.dk or 45 2278 5157. Applications received after the deadline will not be considered. All
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certificates. If you would like additional information about the position, please contact Professor Philip Loldrup Fosbøl on plf@kt.dtu.dk . Applications received after the deadline will not be considered. All
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software and code changes. In the long term we are planning to supervise Bachelor/Master projects and potentially develop courses about effective use of large-scale Storage-, HPC-, cloud- and data management