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electrification and modern power grids. New wide-bandgap semiconductor devices based on silicon carbide (SiC) and gallium nitride (GaN) can switch faster and reduce conversion losses, but their performance is
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neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the economic and environmental cost of AI
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Organizational Unit: Clean Energy Innovation Classification: RO Tenure: Term Duration: Until 31 March 2029 Language Requirements: English Work arrangements: Due to the nature of the work and operational
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on the candidate’s skills and interests, but may include genetically engineering microbes to change form and function, developing theory and AI methods that advance our ability to design reliable, engineered
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Health and Primary Care). This is an opportunity to work with Professor Fitzgerald and her research group, who are internationally renowned for their work on Barrett's oesophagus including the development
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individual expressive behaviours. The project builds on recent work showing that person-specific cognition can be computationally approximated by learning personalised neural architectures or model weights
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We offer you Interdisciplinary work in a highly collaborative environment A unique environment combining state-of-the-art ultrafast experiments at University of Applied Sci-ences and Arts
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promising candidates for this goal, combining fast electrical control, compact device geometry, and excellent performance in a semiconductor platform. As this technology advances, one of the main remaining
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this: new chemistry methods that let around 100 candidate compounds be made, purified and tested for biological activity together, in a single operation taking as little as a week. You will apply this new
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, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our