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create a closed loop pipeline able to rapidly design binders to any target and optimized for developability. The program is rooted in DALSA (DTU’s Arena for Life Science Automation), a new
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-based simulation model for assessing future mobility technologies in the Greater Copenhagen region. Explore the development of machine-learning based scenario discovery for future mobility policy design
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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