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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading
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validation. You will be joining a strong team that works within the following domains: Dynamic turbine response modelling in the multi-body framework HAWC2 Aero-servo-hydro-elastic stability analysis
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atmospheric retrieval and modeling, investigating the effects of stellar activity on atmospheric measurements, and contributing to the preparation of future JWST proposals and publications from ongoing programs
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device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. Exploring hardware-level security mechanisms based
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and validation. You will be joining a strong team that works within the following domains: Dynamic turbine response modelling in the multi-body framework HAWC2 Aero-servo-hydro-elastic stability
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within the following projects: 1. CO2plus: Phase behavior of CO2+X in CO2 storage. 2. CapSim: Optimizing carbon capture simulation through advanced modelling tools. Responsibilities and
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global waterresources is one of the most pressingchallenges of our time, especially under the growing pressures of climatechange and human activity. Global hydrological models are vital tools, but
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute