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projects are multidisciplinary in nature, and the ideal candidates are comfortable with moving outside their field to understand both molecular biology and computational methods. We rely heavily
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develops an adaptive AI-guided XR platform for capturing and transferring expert manufacturing knowledge. Your focus will be on developing AI methods for analyzing and modeling human workflows based on data
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model species, the PhD student selected for this project will investigate unanswered questions on how complex
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utilized to mitigate flooding risks through hydrological modelling and stakeholder engagement.Focusing on the Gothenburg region, the project will: Identify roads suitable for climate adaptation in three
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Modelling and Cognitive Systems, as part of the Linköping University Semantic Web group. The Semantic Web group conduct cutting-edge research in several aspects of the Semantic web, including ontology
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in fluid dynamics, turbulence modeling, CFD, and turbomachinery. Experience with CAD and CFD tools (e.g., Ansys Fluent, CFX, StarCCM+, OpenFOAM). Programming skills (e.g., Python, MATLAB). Knowledge
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/en/organisation/liu/ida You will be placed at the Human-Centred Systems division in the group of Knowledge Modelling and Cognitive Systems, as part of the Linköping University Semantic Web group
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, microbiology or mycology. Familiarity with mycology and the Nordic forest ecosystems is desired. Previous experience with ecology, molecular biology work, bioinformatic and nature conservation are meritorious