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-depth investigation of a class of vulnerabilities and devise static and/or dynamic approaches to detect them in the code or prevent their execution at runtime. Funding category: Autre financement privé
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. The techniques used in the project include protein expression and purification, biochemical characterization, and in vitro reconstitution, cell imaging, western blotting, knock-out/down. Working tasks The senior
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conferences. You will work in a team working on a DSS which requires code and data sharing and good team work. The duties may also include participation in teaching and other departmental work (however, a
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master degree degree is required in relevant areas such as remote sensing, computer sciences, and mathematics. You are also required to have strong background in deep learning for image analysis, e.g
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combination of calcium imaging with optogenetics, in freely behaving animals in Paolo Medini’s lab, in collaboration with Olof Lagerlöf and UmU’s new visiting professor Valentina Emiliani. Tasks
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learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
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Protein Expertise Platform, X-ray, proteomics, NMR (850-400 MHz), cryo-EM and Biochemical Imaging Centre (confocal, SIM, FLIM, spinning disk, TIRF, STORM). Project description Autophagy is an evolutionarily
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intracellular or extracellular bacteria. Analysis of DNA damage markers, levels of m6A machinery (writers, erasers and readers), and host cell response in 2D and 3D culture models by biochemical and imaging
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defects, using both patient samples and model systems (mouse and fly). Implement methods for advanced image analysis. Develop strategies for metabolic tracing in tissues. You will collaborate closely with
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scale. Characterization of ash interactions with products. Imaging and determination of chemical composition with SEM-EDX. Advanced image analysis for quantification of porosity. Multicomponent chemical