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functionalities that can further improve operational performance, such as the integration of predictive models, orbital dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and
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to ongoing work by Dr. Megha Khosla on trustworthy graph machine learning, especially on the relationship between transparency and privacy in graph-based models. Population-scale network data are highly
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Position Data Science and Artificial Intelligence in Cardiac Electrophysiology Our goal: the development of multimodal prediction models to detect and predict atrial fibrillation (AF) and other clinically
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of multimodal prediction models to detect and predict atrial fibrillation (AF) and other clinically relevant cardiac rhythm patterns, predict disease progression and treatment response, and support personalised
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-behaviour literature; consolidating them into a Programme of Requirements; and formulating and implementing a mathematical model that assigns spaces and time slots in response to demand patterns, pricing
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development , various types of leave, and options for sports and cultural activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you
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Materials Science section at TU Delft is actively engaged in developing fundamental understanding for next-generation circular steelmaking. Using advanced atomistic modelling techniques, you will unravel
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the study of vegetation and land use dynamics from local to global scales. Within the Remote Sensing group, we use a combination of advanced methods and modelling approaches applied to the full range
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investment. Overall, the postdoc will contribute to a mechanistic model explaining how bacterial pathogens control the host actin cytoskeleton to drive intracellular motility.
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-generation circular steelmaking. Using advanced atomistic modelling techniques, you will unravel the atomic-scale competition between copper and silicon at grain boundaries and oxide interfaces, delivering