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Field
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to the deep ocean. These canyons are the conduits for transport of land-derived materials to the ocean floor in avalanche-like events called turbidity currents. Turbidity currents transport enormous amounts
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animal movement analyses. Geospatial analysis, GIS, and remote sensing. Statistical, ecological, and machine-learning modeling using modern analytical software (e.g., R or Python). Google Earth Engine and
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large language models, trustworthy AI, and multi-agent systems. Successful candidates will work alongside faculty and PhD students on research tasks that span model development, evaluation, and deployment
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of processing routes for advanced ceramics and surface treatments, with the aim of developing materials and components with tailored properties for demanding applications. SAFRAN is a leading French international
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metrology tools is continuously challenged by stricter requirements and increasingly complex geometries. In this project, you will work on the ideation, modeling, and experimental validation of novel
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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they negotiate changes to their work and business models. Through ethnographic fieldwork you will research what practitioners value within the activity of making creative work, and how that changes
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-driven materials modelling, digital research workflows, and multiscale integration for Waste-to-Value energy conversion systems. As a PhD in AIM, you will help build the first ab initio–based Digital Twin
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propagation in tools used in Friction Stir Welding (FSW) of advanced steel pipelines. The research activities include: Development of thermo-mechanical finite element models for Friction Stir Welding tools
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living