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Join a research team working on next-generation multimodal AI models for real-world use in healthcare, automotive, and other safety-critical domains. The position offers hands-on work with deep
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will perform computational modeling of perceived safety and comfort zone boundaries based on in-project data collection from drivers. The modeling will be both rule- and machine-learning/AI based
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importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models that will quantify the mechanisms, precursors and the time to failure. This will be
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interfaces. About us The Condensed Matter and Materials Theory division models and studies diverse materials and condensed matter systems, often inspiring new materials, technologies, or structured media with
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The aim is to unravel the anthropogenic and natural processes, and their relative importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models
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research and modelling approaches, and in close collaboration with relevant stakeholders.Achieving our vision is based on creative collaborations within the framework of a good and equal working environment
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. The division's work requires interdisciplinary efforts, which is reflected in our team's composition spanning engineering, natural, and social sciences. We are united by applying systems-based approaches and
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and development. Project overview The ongoing transition from synchronous machine-based generation to converter-dominated renewable energy sources presents new challenges for the operation, control, and
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environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with
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multiple engineering fields to address an essential need in healthcare. About us At the biomedical electromagnetics group , we conduct world-leading research in the development of microwave-based