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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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chemical analysis is a holistic tool to characterize chemicals but struggles with very persistent and very mobile substances (vPvM) like ultra-short chain PFAS and trifluoroacetic acid. These substances
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AI models. Identifying relevant modalities to enhance prediction performance, with a focus on multi-spectral sensors, will be a key research area. Additionally, anomaly detection for modalities other
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include quality assessment, processing and filtering of different data modalities, and co-supervision of junior researchers in the group. You will have the opportunity to develop your own research ideas and
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and photon indistinguishability towards unity. The primary responsibilities of the PhD students include: Employ numerical simulation techniques based on Fourier Modal Method and the Finite Element
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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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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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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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diversity. We are looking for a motivated applicant with good competences in operation research who wants to gain hands-on experience in cutting-edge energy modeling and analysis to be part of the Ports as
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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