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on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics
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investigating pain in former athletes, master’s athletes, and nonathletes; the postdoctoral fellow will assist in launching this study and in data collection and analysis for this study. Duties and
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interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD in one of the following: Data Science, Computer Science, Computational Social Science, Information
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to have the following skills and experience: Essential criteria First degree and PhD in a relevant discipline such as pharmacy, medicine, drug delivery, pharmaceutical analysis A sound (theoretical and
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for three weeks of training in higher education teaching and learning. These tasks will be performed: Analysis of time series of active fire and burned area data together with ancillary datasets (e.g. biomass
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. Primary processing of single cell and spatial transcriptomics data, and more project-focused in-depth analysis. Integrate existing single cell and spatial transcriptomics datasets, use publicly available
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Postdoc Position in Models of Quantum Programming Languages (Sapere Aude: DFF-Research Leader Pro...
, and Programming Languages (ACP ), the section on Topology, Algebra, Analysis and Geometry (TAAG ) and the Centre for Quantum Mathematics (QM ). The proposed starting time is Winter 2026, with some room
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at large-scale, data-driven legal analysis. The broader goal is to extract structured knowledge from legal texts and enable empirical research, particularly in the area of international human rights law. The
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data sets and climate model outputs Analytical skills, including experience with multivariate analysis, time-series, and geospatial statistics Previous research experience and publication record Ability
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, data analysis, and modelling, in collaboration with the University of Southampton and the National Physical Laboratory (NPL). With a background in Materials Science, Physics, Chemistry, or Engineering