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and treatment; (5) opinion dynamics. DESCRIPTION Functional Area 1: Research Percent Effort: 70% Perform analysis of applied mathematical models relevant to the project. Develop, implement, and optimize
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National Laboratory's National Synchrotron Light Source II (NSLS-II) seeks a Postdoctoral Research Associate for AI-driven Structure Analysis for Biological Discoveries for an on-site position in
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have: you will own the bacterial side of the project. You will work with our full infrastructure for vesicle assembly, synthesis and interaction analysis, with access to IBEC’s BSL-2 facilities, and in
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research and development in the areas of gauge field generation, linear and eigen-solvers, or novel analysis methods. This position will reside in the Advanced Computing for Nuclear, Particle and
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. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related discipline, with demonstrated knowledge of or research experience in
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and physical modelling. The goal of this position is to develop data-driven approaches to AI-based analysis of complex interaction systems and suitable hybrid architectures for this purpose
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workflows. The goal of this position is to develop data-driven approaches to AI-supported analysis for applications in ESS as part of the EU project “GenAI4Earth.” To this end, current developments in
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stakeholders involved in planning and decision-making. Qualifications Candidates must have a PhD in atmospheric physics, hydrology, meteorology, Earth system science, climate studies, applied mathematics
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of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and
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learning for the analysis of population-scale networks. The position focuses on two pillars of trustworthiness: explainability and privacy-preserving learning. This research direction connects closely