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analysis. The project is funded by the Danish National Defence Technology Centre (NFC). The project is a collaboration between DTU, the Alexandra Institute and Copenhagen University’s expertise in AI-driven
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updating and data extraction Work with quantitative data analysis, including meta-analysis Integrate living systematic review data into a RBA of sustainable dietary transitions Develop a living support
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observational data Sample analysis in the laboratory using state-of-art molecular microbiology techniques and fish health and welfare analysis Sequencing data analysis (bioinformatics) Scientific dissemination
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energy modeling and analysis to be part of the Ports as Energy Transition Hubs (POTENT) Marie Sklodowska-Curie Actions Doctoral Network. The network will consist of 15 PhD candidates interested in
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potential market failures and prevention mechanisms. You will be combining theoretical analysis with practical applications, involving mathematical modeling, algorithm development, and coding. You should have
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Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
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analysis of dynamic systems of oligosaccharides; biophysical studies using spectroscopy (NMR, UV-Vis, fluorescence and CD spectroscopy) to investigate conformation, binding phenomena and self-assembly
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working with live animals. Excellent skills for data handling and statistical analysis. Strong written and oral communication skills in English. Ability to work both independently and as a part of a team
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22 Aug 2025 Job Information Organisation/Company Technical University of Denmark Department Department of Civil and Mechanical Engineering Research Field Engineering Researcher Profile First Stage