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Field
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Are you a highly-motivated researcher looking for a PhD position in complex dynamical systems and want to make some impact? If yes, the analysis group of the Korteweg-de Vries Institute
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will develop new methods for causal inference in complex longitudinal survival data, with applications to nationwide Danish health registries. The project focuses on dynamic and asynchronously initiated
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Are you excited about the future of wearable healthcare? Join us to merge microfluidics and contact lens technology, developing smart lenses that enable controlled tear fluid collection and analysis
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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of interest are harmonic analysis, operator theory, computer algebra, optimisation and complex analysis. Other key research themes at the department are mathematical statistics, applied mathematics, computer
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will
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, Mathematics, Engineering or a related discipline, with an interest in AI applied to complex and safety-critical systems. Good knowledge of Machine Learning and Deep Learning methods, including experience with
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-of-the-art in failure propagation analysis and safety assessment of complex systems. In particular, it will investigate extensions of existing formalisms to deal with aspects such as the timing of fault
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Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Job