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computational methods to predict novel, disordered materials with application, e.g., for solid electrolytes in next-generation batteries. The position is part of the Villum Young Investigator project titled
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At the Technical Faculty of IT and Design, Department of Computer Science, a 2-year Postdoc position in theories for programming semantics, methods for verification and reliability assurance
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. Read more about CEBE (https://villumfonden.dk/en/nyhed/billion-kroner-research-grant-accelerate-green-transition-built-environment). The transition from CO2 producing building materials to renewable, CO2
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
materials, including their hygrothermal properties, durability, and performance limits in building applications. Competence in laboratory testing and development of test methods is essential, as is experience
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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scientific and technical supervision to students and technical staff. Facilitate collaborations and ensure alignment between experimental and computational research teams. Your competencies The ideal candidate
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of electromagnetic theory, microwave principles, and computational electromagnetics (FDTD, FEM, MoM). Research experience with mechanically beam-steering, multiband/shared-aperture antennas, or antenna array synthesis
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learning, for offshore industrial produced water treatment processes. The developed methods/solutions should be tested and demonstrated on a globally leading pilot-plant sited at Aalborg University
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and high-performance computing resources. The positions are part of the AI RF Sensors research group, which develops AI-driven methods for RF, microwave, and wireless technologies in close collaboration
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-experimental data from five countries. Methodologically, the project designs and implements survey experiments and other causal inference methods (e.g. difference-in-differences and synthetic control). Your