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                Employer- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Delft University of Technology (TU Delft); yesterday published
- Leiden University
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- University of Amsterdam (UvA)
- Eindhoven University of Technology (TU/e); Eindhoven
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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- Delft University of Technology (TU Delft); today published
- Eindhoven University of Technology (TU/e); 4 Oct ’25 published
- Eindhoven University of Technology (TU/e); today published
- Eindhoven University of Technology (TU/e); yesterday published
- Maastricht University (UM); 27 Sep ’25 published
- Radboud University Medical Center (Radboudumc); Nijmegen
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- University of Groningen; 26 Sep ’25 published
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                the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from 
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                the entire system, where many interconnected modules affect each other. In this project, you will be designing algorithms to guarantee the reliable operation of semiconductor machines, together with a highly 
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                algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine learning is also desiered. TU Delft (Delft University 
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                30 Sep 2025 Job Information Organisation/Company University of Amsterdam (UvA) Research Field Computer science » Informatics Computer science » Programming Mathematics » Algorithms Mathematics 
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                . Experience working on inversion problems (e.g., MCMC type algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine 
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                : questionnaires on healthcare and patient outcomes, qualitative data on patient experiences, improved diagnostics using innovative laboratory methods, development of pathophysiology-based treatment plans 
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                millions of US Dollars. Ensuring that contracts cannot be exploited is critical. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity 
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                using innovative laboratory methods, development of pathophysiology-based treatment plans, identification of biomarkers and haemostatic modifiers with multi-omics approaches, an AI-driven bleeding 
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                exploited is critical. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity language. While our current digital infrastructure relies 
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                oriented towards the development of a domain-specific design automation framework for cryptographic hardware. Your work will focus on identifying the mathematical knowledge and properties to guide hardware