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-preserving data analysis. We are looking for a PhD student to join our team and contribute to cutting-edge research in theoretical computer science, with a focus on Secure Multi-Party Computation. You will
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frameworks and methods such as 1D-CNNs, transformers, or chemometrics for spectral analysis is highly valued, though applicants with strong backgrounds in physics, physical chemistry, or analytical chemistry
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, project-based innovation, and specialist support come together. Among other things, the teams offer access to HPC and HTC environments, storage, processing and analysis capacity for large-scale datasets
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Description Challenge: Uncovering the interdependency between telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency
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that structural neglect through an interdisciplinary, participatory research program that combines empirical research, legal and policy analysis, and technology assessment. Grounded in a Theory of Change approach
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genome instability and metabolic diseases. The responsibilities of the position include: Establish the aforementioned research line Design and perform investigations and data analysis Working closely with
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observation (EO) and explainable artificial intelligence (xAI) for decision intelligence. In an era of rapidly evolving geopolitical dynamics and increasing complexity in the security landscape, the ability
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on monitoring complex, superposed deformation signals caused by deep subsurface processes (gas storage, production, and injection) and shallow processes (soil compaction, groundwater dynamics), using satellite
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of correlates of disease to pathogens Understanding the virulence mechanisms of complex pathogens is still needed because these pathogens circulate in livestock and wild animal populations. Effective vaccines
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of the parameter space in relation to the statistical model. One of the main goals of SLT is to quantify the complexity of such models w.r.t. the data generating process (and some prior probability distribution