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This project targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification
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knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material properties and manufacturing processes for mainly metallic components, specifically cast
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of the European Partnership on Animal Health and Welfare (EUPHAW) and focuses on the development of methods to quantify and analyze behavior and welfare in dairy cattle using large-scale video and
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European Universities in several EU aviation projects About the research project EXAELIA The project is related to the development of future aircraft concepts and propulsion technology that has
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response.' Lab website: https://ki.se/en/neuro/lopez-laboratory-neurobiology-of-stress-and-treatment-response Your mission We are looking for highly motivated candidates to join our team and work with
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degree, obtained within the last three years prior to the application deadline Experience of teaching at undergraduate or master’s level, and an interest in further development within teaching and
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, etc.) development of predictive models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data sources, uncertainty
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such as the heart and nervous system, invariably with fatal consequences. The project will focus on probing the molecular factors underlying this instability (see for example https://www.nature.com/articles
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inclusive work environment with excellent opportunities for professional development. About the position Type of employment: Fixed-term employment according to the postdoctoral agreement. Scope: 100% (80
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, physics-informed control, and digital twin technologies. Project description The project focuses on the development of robotic methods for plant health monitoring that combine robot–plant interaction with