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these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/postdoc-in-laser-process-monitoring-… Requirements
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. Empa is a research institution of the ETH Domain. The Laboratory of Advanced Materials Processing (LAMP) is a multidisciplinary research unit that develops innovative functional modification of materials
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the lab, and at the same time to play an active role in shaping and creating an inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en/Research/Values
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. Empa is a research institution of the ETH Domain. In our research group, we transfer membrane and encapsulation strategies from academia to industry. Solution-based processes like electrospinning and
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project “DepoIon”, we develop physical vapor deposition (PVD) process control for solid state battery relevant material coatings. Your tasks You will work on basic science topics as well as on applied
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
ecosystem processes, in particular deadwood decomposition, in forests are altered by global change factors such as climate change, disturbances, and management-induced structural changes at different spatial
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interferometry, isothermal titration calorimetry, or similar) and cellular assays. Expertise in bioinformatics and programming is advantageous. Experience in structure-based design or generative models is a plus
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between behavioral and computer scientists. The ideal candidate has some knowledge in both areas, and the specific behavioral domain is open to discussion. Project B – Understanding and Countering
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system capable of preparing and processing the cornea. In this project, the postdoctoral candidates will be responsible to develop an optical coherence tomography (OCT) integrated with a laser ablation
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, for a Postdoc in climate impacts on hydrological extreme events 80-100% (f/m/d) You will develop data-driven and/or process-based models to assess climate impacts on extreme events, their drivers, and/or