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of chemical data. Key Responsibilities: Utilise high data-density reaction/bioanalysis techniques, including high-throughput experimentation, to inform and enhance drug optimisation. Employ machine learning
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and projects. Responsible. Good English writing (and speaking) skills. Additional qualifications Experience in the analyses of large-scale human population genomic data. Experience in using standardized
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against known target antigens and identify novel targets of autoimmune responses to stratify patients, (2) recognize mechanisms of actions of immunomodulatory drugs applied to patients with MS and related
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combination of different methods such as population genetics, analyses of fungal environmental DNA and soil spore banks in soil to find out about the life histories of ectomycorrhizal fungi in general, and
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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no research. We propose to leverage state-of-the-art techniques to measure how young brains track information content within screen media in real-time. The project will involve collecting and analysing EEG
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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Degree Dr rer nat (Doctor of natural sciences) Course location Münster Teaching language English Languages Courses are held in English. Mode of study Less than 50% online Programme duration 6
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for the Fraunhofer-Bessel Research Award. As soon as we receive all the necessary documents, we will confirm receipt of the nomination by e-mail and initiate the review process. All information will of course be
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using LP-TEM Execution of TEM analyses as part of our TEM facility at HI ERN Presentation of scientific results at national and international conferences as well as publication in peer-reviewed journals