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-resolved fluorescence methods for studying protein-protein interactions and protein structure-function relationships in live cells. This project will focus on elucidating the structure-function mechanisms
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capitalizing on this insight. A similar system as described above for ammonia has also been established for or CO2 hydrogenation where we also have a long tradition for work on both the fundamental level as
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architectures) to large-scale biomedical datasets. These models will be used to work with different types of data from the healthcare and biological domains, including genomic profiles, and clinical event
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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Development & Maintenance: Drive the development, optimization, and upkeep of the lab's computational tools and analysis pipelines, ensuring that they robustly support and accelerate the team's research
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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Fluid Balance: How do lymphatics fine-tune the equilibrium between immune tolerance and inflammation? How the optimal interstitial fluids? How the resolution of inflammation and edema? Phenotypic
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for internal and external projects, bringing it up to industry standards. You will Develop and optimize the specificity assay for biologics, with technical support. Identify and assess innovative applications
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Disease. The antibodies will be engineered for optimal target engagement. The work involves a close collaboration with PI Dr. Simon Glerup (CSO, Draupnir Bio ApS) and Assoc. Prof. Nathalie Van Den Berge