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the applicant and the Department of Ecoscience. The position concludes after 24 months. Job description The Department of Ecoscience, Aarhus University is looking for a post-doctoral researcher to optimize a
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development, maintenance, and optimization of the advanced spectromicroscopy systems at the MAXPEEM beamline. Provide high-level experimental support and technical guidance to international visiting researchers
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optimization of the advanced spectromicroscopy systems at the MAXPEEM beamline. Provide high-level experimental support and technical guidance to international visiting researchers (beamtime users). Research
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processes based on CO2 and other carbon-rich waste streams enable net-zero CO2-conversions into valuable chemicals. This project aims to design, integrate and optimize metabolic pathways in an engineered C
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in quantum methods for bioinformatics. Topics may include, but are not limited to, solving hard combinatorial optimization problems with quantum methods, quantum-based data structures (e.g. in
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Commissariat à l'Energie Atomique et aux Energies Alternatives - Groupe | Gif sur Yvette, le de France | France | 4 days ago
techniques including synchrotron radiation induced Hard X-ray photoelectron spectroscopy and complementary structural analysis including high-resolution electron microscopy, X-ray diffraction and near field
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in porous media. The researcher will contribute to the implementation of new physics (such as transport, reactions, and thermo-mechanical couplings), computational performance optimizations
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Responsibilities Develop, test, and optimize AI-driven pipelines for 3D reconstruction and rendering. Implement and evaluate neural rendering techniques using real-world digital heritage datasets. Collaborate with
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extensive electromagnetic modeling to optimize the waveguide structures for minimal loss, efficient confinement, and effective mode matching with external optical components. Particular attention will be
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Research Infrastructure? No Offer Description TASKS/ROLE * conducting research under the project Design-ready forward and inverse surrogate modeling of high-frequency structures using deep learning and