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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than
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climate risks coupling with machine learning techniques and physics models. The successful candidate will have a demonstrated background in computer science, statistics, and engineering as exemplified by a
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!', which involves 9 PhDs and 5 Postdocs. So, we offer an excellent inspiring, collaborative, and international research environment, with access to leading experts in medical technology and AI-driven
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simulation-driven software systems, from data ingestion and model development to experimentation and deployment. Hands-on experience with machine learning frameworks, particularly PyTorch, including model
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of occupations, driven by digital transformation, the emergence of generative artificial intelligence, and ecological transitions, is challenging the alignment between the competencies developed in higher
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through the creation of sophisticated 3D CAD models and detailed design packages suitable for fabrication. This position resides in the Plasma Enrichment Deployment & Engineering Group in the Plasma
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steel or aluminium structures Welding, fabrication, or construction automation Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven methods for engineering
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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that interects additive manufacturing, dental prosthetics, surface engineering, process monitoring, digital traceability, and data-driven modelling. The candidate will receive advanced training in the following
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of Arctic Phytoplankton, within the Research Council of Finland-funded project on "Climate-driven Dispersal, risk or potential for Arctic diversity". The position is full-time, and the preferred starting date