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Field
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emerging research field that uses machine learning, data analysis and computational modelling to guide the discovery, characterization and optimization of new materials. By accelerating innovation cycles, AI
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University alliance project UNIVERSEH 2.0 (European Space University for Earth and Humanity): https://universeh.eu/ UNIVERSEH 2.0 aims to further develop and strengthen the alliance’s position as the leading
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inference, longitudinal methods, survival analysis, regression modeling, machine learning, or prediction modeling are required, as well as experience with statistical software such as R, SAS, or STATA
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, C++ or similar languages. Good knowledge of network communication and integration between different systems, such as robots, AI and digital twins. Good knowledge and experience of machine learning
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well as within security for critical infrastructure. More about research and eduction in cybersecurity at Linköping University is found here: https://liu.se/en/research/cybersecurity As Assistant professor in
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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more on the University website about being a Lund University employee. https://www.lunduniversity.lu.se/about-university/work-lund-university Are you ready to help shape the future of research? Learn
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learning and deep learning models for trait prediction and climate-resilient wheat breeding. Analyze time-series UAV data using crop models in combination with genomic and agronomic information. Collaborate
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: detection of objects and relations between objects, and use of these relations to infer new knowledge (i.e. reasoning); (ii) explore object affordances, learn the consequences of the actions carried out and
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on practice-based school research within the framework of ULF (Education, Learning & Research, ulfavtal.se ). The purpose of the initiative is to strengthen the long-term development of the Swedish school