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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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pulses develop numerical codes to calculate the system dynamics by solving partial differential equations (e.g. Schrödinger equation, von Neumann equation) model the coupling to lattice vibrations (i.e
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of mechanics, including mechanical properties of materials, strength and vibration analyses, thermodynamics, fluid mechanics, safety theory and control engineering. The research under the section of Materials
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, ornithology, molecular techniques, or data analysis is desirable.� �ENTRY REQUIREMENTS At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5
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-house powder diffraction. Use in-house imaging experiments for detailed morphological analysis of the battery cells. Perform in situ and operando synchrotron X-ray diffraction and imaging studies
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: Hands-on experience with proteomics workflows and mass spectrometry-based data analysis. Basic knowledge of protein biochemistry and enzymology. Familiarity with machine learning frameworks (e.g., PyTorch
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the research group Bioactives Analysis and Applications, and as part of the prestigious Alliance PhD program, you will collaborate with the Technical University of Munich (Germany). If you're ready to
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understanding of environmental assessment and are comfortable working in a laboratory environment. A background in chemical risk assessment (including exposure analysis, analytical chemistry, ecotoxicology, and