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group which is responsible for the development of the Ambient Pressure X-ray Photoelectron Spectroscopy Program at MAX IV. The beamlines provide a wide range of sample environments for in situ and
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researcher is intended to enable persons who have recently been awarded their doctoral degree to consolidate and develop primarily their research skills. Besides consolidating their research and publication
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generation, and explainability Evaluation methodologies for knowledge-intensive AI systems The project will be driven by real-world domain applications in materials, casting, and manufacturing, developed in
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by
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social robots, as well as how children’s understanding of AI develops over time. The postdoc project is part of the recently established multi-site research group Child Development in the Age of AI and
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–environment systems. A central component of the project is the development of next-generation process-based eco-epidemiological models that explicitly integrate environmental variability, ecological
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human health. The lack of discovery of new modes of action, increasing costs of registrations, and development of resistance among weeds and pests, further limit the prospects for relying on chemical
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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losses, but are increasingly scrutinised and regulated due to risks to the environment and human health. The lack of discovery of new modes of action, increasing costs of registrations, and development
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science