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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for improved cancer understanding, diagnostics, and
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become increasingly prominent in space applications, offering substantial benefits with high strength/stiffness and lower density/weight compared to metallic structures. Their use space vehicles span
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composition of the nectar. Despite the importance of pollination for seed production of many brassicaceous crops, little is known on the role of the nectar microbiome for plant fitness and seed set in
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almost every product we use, mathematics, electronics and computer technology contribute to all of society's activities. The faculty works together intensively with industrial and medical partners
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well as topics in phylogenetics. This project will involve working closely with experimentalists, and will be co-supervised by Prof Gerald McInerney and Dr Daniel Sheward, who have expertise in virology and
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at the intersection of cyber security, cyber-physical systems, and mathematical methods as part of the NORCICS Norwegian Centre for Cyber Security in Critical Sectors. The centre links researchers from
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Supervisors: Prof. Reinhard Maurer (Chemistry), Prof. Richard Beanland (Physics) Understanding how local atomic structure and long-range emergent magnetic and electronic properties in defective 2D
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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. Information For information you can contact: Prof. Michele Cucuzzella (for inquiries about the position), m.cucuzzella@rug.nl (please do not use the email addresses above for applications)
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle