299 algorithm-development-"Helmholtz-Zentrum-Geesthacht" PhD scholarships in Netherlands
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- University Medical Center Utrecht (UMC Utrecht); Utrecht
- University of Amsterdam
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ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance
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partners: ASML and DCODIS (a start-up). This is technically challenging applied research with as main outcome a proof-of-concept tool that allows developers to quickly find and fix software errors including
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tool that allows developers to quickly find and fix software errors including security vulnerabilities. You will innovate the Find2Fix pipeline by making the different steps, including found issues and
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4 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science Mathematics » Algorithms Mathematics » Statistics Researcher Profile First
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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transparency and trade secret claims of regulated actors? And explore legal arguments in support of algorithmic transparency and data access for public interest research? How does EU law balance transparency and
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, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge through interactive learning. For this we will build on the minimum description length (MDL
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well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient
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, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge through interactive learning. For this we will build on the minimum description length (MDL
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant