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transformation pathways. Develop and implement suspect analysis and non-target workflows for the identification of transformation products (TPs) in real-world samples using data obtained by LC-MS. Create digital
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this position, you will advance an innovative drug discovery workflow to enable the identification of membrane receptor ligands. This project is a collaboration between the Pomplun lab and the Heitman labs and
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these questions will involve close collaboration with international experts and the use of rich administrative data for the Netherlands. The project places a strong emphasis on causal identification, applying state
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, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models. The postdoctoral researcher will be responsible for: Developing a
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responses are converted into biochemical signals. This research might include the identification and characterization of signaling proteins, investigating the effects of genetically modifying these proteins
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the characterization of molecules that are present in cells and allows thereby the identification, quantification and characterization of proteins and other biomolecules that work together and are involved in all
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pathogenesis of both Parkinson's, as it is the primary protein constituent of Lewy bodies. Early and accurate identification of Parkinson's is crucial for tailoring therapeutic strategies (for example
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linear fractional representations; Model identification, validation and uncertainty quantification; Set up the performance and stability analysis frameworks to verify the DFAOCS performance and stability
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are recruiting a highly motivated postdoctoral researcher to lead the first implementation of Deep-UV Raman spectroscopy for real-time polymer identification. This project addresses a critical gap: no established