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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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) and space-time boundary element methods (BEM), which both discretize the PDE as a whole, treating time as yet another dimension. In particular, this allows for fully flexible local mesh refinement in
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courses attended and grades obtained, and, if applicable, a list of publications and references. Links to representative code you (co-)developed, e.g. on GitHub. Alternatively, you may upload a zipped
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multiple brain areas in an optimised way. This may include neural network and neural mass modelling of large-scale brain activity during and after stimulation, and experimental tACS in healthy participants
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coordination across many stakeholders. You will work in a strong multi-actor consortium with University of Twente (UT), Tilburg University, Saxion, regional networks (e.g., Pioneering, Midpoint Brabant
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, 2020 . In this PhD project you will work on applying RNPU networks for solving computational problems that are considered hard. Information and application Are you interested in this position? Please
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occurs; and validating these approaches against community and industry benchmarks. The work combines network measurements, data science, and systems security, with an emphasis on reproducibility and real
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content, the execution of malicious code on connected devices, or the abuse of limited resources. The idea is to assess the resistance of these models against new attacks, using techniques coming from