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on the theory of deep learning will investigate questions such as the structure and expressivity of emerging neural architectures relevant to space, such as implicit neural fields, continuous normalising
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leave, and partially paid parental leave; working hours that can be discussed and arranged so that they allow for the best possible work-life balance; there is a strong focus on vitality and you can make
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that can serve as references for future studies, (ii) enhancing the understanding of physical mechanisms and causal pathways to strengthen attribution analyses and model development, build operationalized
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strong focus on vitality and you can make use of the sports facilities available on campus for a small fee; a fixed year-end bonus of 8.3%; excellent pension scheme. In addition to these first-rate
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develop a strong academic profile. You will build valuable connections by participating in both academic and social activities of our PhD and postdoc community. This is wat you'll be doing You will be part
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collaborators with whom you will regularly exchange ideas about your research. This will help you develop a strong academic profile. You will build valuable connections by participating in both academic and
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and to the world around us. Make the most of our bicycle budget, or join networks such as Young@EUR , FAME or QuEUR. Time and space for your development in the broadest sense: development days and a
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scarce or specialised. This project aims to develop the next generation of adaptive visual learning systems by enabling foundation models to efficiently specialise through the exploitation of structure
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enabling foundation models to efficiently specialise through the exploitation of structure within representations and across tasks. The resulting methods will help bridge the gap between general-purpose
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that autonomously optimise EO systems tasking and data collection, using decision intelligence to make real-time decisions based on environmental signals and predictive models; contribute to the rapid prototyping and