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planar optical waveguide structure. The current project focuses on advancing a surface-sensitive, label-free waveguide scattering microscopy (WGSM) platform for nanoparticle characterization in advanced
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optical waveguide structure. The current project focuses on advancing a surface-sensitive, label-free waveguide scattering microscopy (WGSM) platform for nanoparticle characterization in advanced therapies
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at the Division of Chemical Physics is at the forefront of synchrotron-based operando investigations of defined model catalyst surfaces for energy conversion, both in thermal and electro catalysis. The operando
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responses, governance models, and ethical frameworks shaping the integration of AI in higher education. We especially encourage research that combines socio-technical perspectives with quantitative methods
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reasoning, conceptual understanding, and self-regulation in learning. Institutional responses, governance models, and ethical frameworks shaping the integration of AI in higher education. We especially
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this project, you will become part of a team of researchers working on fundamental aspects of data-driven decision-making inspired by, and applied to, problems in healthcare. Currently, we are investigating
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of electrodes and catalysts for low temperature fuel cells, electrochemical hydrogen generation, batteries, as well as heavy metal removal from aqueous solutions. By designing well controlled model systems in
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generation, batteries, as well as heavy metal removal from aqueous solutions. By designing well controlled model systems in combination with powerful analysis and characterization techniques, improved
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of Geoscience and Remote Sensing , we develop advanced methods and instruments to observe and understand the Earth system. Combining satellite, airborne and ground-based measurements with modelling and machine
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. The current position deals with free-space optical transmission experiments. It will involve challeges with low SNR, atmospheric turbulence issues, coherent recevers and related signal processing algorithms