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and genetic investigations, no underlying hemostatic defect can currently be identified in approximately 50% of these patients. This may be further improved by evaluating clot degradation (fibrinolysis
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, they have the potential to solve certain computational problems far more efficiently than classical machines. Realizing this potential requires entirely new numerical algorithms that combine advances in
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. These differences are partly driven by genetic variation, which influences cellular pathways involved in toxicity. Understanding this variation is essential for developing future safety testing strategies
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products, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and
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ones for different stakeholder groups, as a basis for policy making? Are you interested in spatial optimization algorithms and uncertainty assessment? Then this PhD position at the Department of Human
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, genetics, immunology, and social sciences to develop evidence-based, personalized donation strategies. Within this multidisciplinary project, you will play a central role in the work package focusing
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of probabilistic and extremal combinatorics, structural graph theory and algorithms. We study problems on discrete structures such as graphs, permutations, posets or set systems using probabilistic, structural and
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. During the PhD, you will work on topics at the intersection of probabilistic and extremal combinatorics, structural graph theory and algorithms. We study problems on discrete structures such as graphs
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pose estimation algorithms. The models and algorithms you develop will be part of open source and data repositories affiliated with the broader research program and TU Delft’s commitment to Open Science