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simulations, computational modelling, and/or data-driven analysis to assess the impact of different climate policy pathways. Developing interactive AI-based narratives that communicate climate risks in ways
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mapping, and scenario analysis. The project is led by Professor Frank Dignum (main supervisor) and Dr. Jason Tucker. Requirements The general admission requirements for doctoral studies are a second- cycle
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. The candidate will be engaged in synthesis of new materials and characterization of these materials using BET/DFT surface area analysis, DSC, x-ray diffraction, Raman and IR spectroscopy etc. It is also planned
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experience in standard biochemical analysis methods, advanced molecular cloning techniques, CRISPR/Cas9 and experience in culturing and transfection of eukaryotic parasites. Experience in light microscopy
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and/or dynamic approaches to detect them in the code or prevent their execution at runtime. Keywords for this project: code analysis, static analysis, reverse engineering, defense mechanisms
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purification, and computational image analysis must be acquired before starting PhD project work. As a PhD candidate, you must also be fluent in both oral and written English. Merits are: Skills and experiences
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areas, of which at least 30 credits must be at an advanced level. Courses in statistical analysis, quantitative methods, or mathematical models acquired outside these subject areas may also be included
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valuated. Experience in programing in image analysis or a willingness to develop such skills is considered an asset. Please visit the lab website of Lena Svensson. You should be highly motivated and able
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cytometry, FACS, and qPCR for quantifying infection; as well as statistical analysis. You are also likely to use CRISPR/Cas9 technology, CLIP assay, co-immunoprecipitation, and other biochemical methods
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at least 30 credits must be at the advanced (master's) level. Courses in statistical analysis, quantitative methods, or mathematical modelling obtained outside these subject areas may also be included