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of researchers. The end of data taking being scheduled for January 2027, the student will make a significant contribution into data analysis toward the publication of the final results. The work will
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. The successful candidate will work closely with academic and clinical collaborators to support the collection, management and analysis of multimodal research data. The project will investigate the combined use
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qualifications Experience in one or more of the following areas is considered a merit: data analysis using ROOT, particle-transport simulations using Monte Carlo codes such as Geant4, FLUKA, or OpenMC, nuclear
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for the analysis of complex multi-omics datasets. Present and discuss research findings within the team and at national and international scientific conferences. Contribute to scientific publications in leading
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resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will
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strong asset.•Experience in the analysis of high-dimensional biological data (single-cell or spatial transcriptomics, digital pathology or biomedical imaging) is an advantage.•Comfortable working on Linux
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, digital methods and discourse analysis to examine transnational collective action among European Muslims. It will aim to understand how European Muslims actively shape, negotiate claim, contest their sense
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coastal sediments and their role in polar biogeochemical processes. Your main responsibilities will include: Sampling and geochemical analysis of Antarctic sediment samples Incubation experiments and stable
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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protocols and lead data analysis and interpretation for assigned research questions within the TB screening portfolio; author manuscripts for peer-reviewed publication Contribute to prospective data