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Field
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of flexible energy resources (e.g., heat pumps); knowledge of mathematical modelling, optimization, machine learning, or data analytics (experience in one or more is desirable); strong scientific programming
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and analytically strong researcher with a broad interest in climate, land use and sustainability. You quickly acquire new knowledge, critically assess complex information and communicate your findings
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applicability. By bridging machine learning, behavioural science, and clinical research, the project seeks to establish foundational methods for trustworthy agentic AI systems that can be deployed across diverse
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programming (e.g., Python, MATLAB, or similar). Experience with image analysis and/or AI methods is a plus. Strong analytical and problem-solving skills. Ability to work independently as well as in a
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. We are seeking a candidate motivated to explore the how emerging technologies – such as machine learning, generative AI, and extended reality (XR) – impact societal preparedness planning required
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Experience Assessment Methodologies for Intelligent Realities • Research Theme B: Novel Environment and Interaction Techniques for Intelligent Realities • Research Theme C: Visual Analytics for Intelligent
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be favorably considered. If you are a non-Swedish speaker, we expect you to try to learn Swedish when you start your position (SLU arranges Swedish courses). Emphasis will be placed on personal
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models and observations yet still rely heavily on precomputed risk maps. Deep learning has improved flood mapping, but many models remain event-specific and transfer poorly between regions. Geospatial
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. Coding and hardware skills are desirable. Strong analytical/mathematical skills. Passion about research and willingness to learn. Good presentation, communication and writing skills. Funding support After
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differences and metabolic disease. Strong analytical and organizational skills. Ability to work independently within a multi-disciplinary, international team. Excellent written and spoken English. What we offer