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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); yesterday published
- Delft University of Technology (TU Delft); 3 Oct ’25 published
- Delft University of Technology (TU Delft); yesterday published
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- University of Amsterdam (UvA); Published today
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3 Dec 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Mathematics » Discrete mathematics Mathematics » Geometry Researcher Profile First Stage
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developing new explanation methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as
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. Knowledge of mathematical machine learning theory or mathematical statistics is a plus, as are extra-curricular activities in, for instance, student associations, sports, music, etc. Prior knowledge
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18 Oct 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Mathematics » Probability theory Mathematics » Statistics Researcher Profile First Stage
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. Knowledge of mathematical machine learning theory or mathematical statistics is a plus, as are extra-curricular activities in, for instance, student associations, sports, music, etc. Prior knowledge
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of mathematical machine learning theory or mathematical statistics is a plus, as are extra-curricular activities in, for instance, student associations, sports, music, etc. Prior knowledge of explainable AI is
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needs to be supplied with rigorous uncertainty analysis. The focus of this project is on the mathematical theory enabling these advances, via asymptotic analysis and nonparametric modeling. You will work
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of thousands of software engineers. Across several tracks, we will develop tools that rethink the future of software engineering. Our work will be informed by sound theories and supported by empirical data. In
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of thousands of software engineers. Across several tracks, we will develop tools that rethink the future of software engineering. Our work will be informed by sound theories and supported by empirical data. In
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. Our work will be informed by sound theories and supported by empirical data. In this project, we will use AI as an opportunity and address the challenges that emerge due to AI. Our goal is to conduct