20 algorithm-development-"Prof"-"Foundation-for-Research-and-Technology-Hellas" PhD positions in Netherlands
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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- University of Amsterdam (UvA)
- University of Groningen
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); today published
- Eindhoven University of Technology (TU/e); Eindhoven
- Erasmus University Rotterdam
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); Published today
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning
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students to become experts in a specific domain of choice. This vacancy is explicitly targeted at candidates interested in algorithmic biases and developing methodological approaches to tackle this challenge
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tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics, top quark physics, and searches for new physics signatures. This is what you will do After the discovery
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(FELIX) for ATLAS detector systems. The group also has a strong record in track reconstruction, flavour tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics
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to test and demonstrate the developed concepts and algorithms for integrated (re)planning. This PhD research will use a mixture of techniques from logistics, operations research, multiple-criteria decision
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well as develop new algorithms for inverse scattering. These extensions will be employed in a reconstruction process on actual measured data from real-world metrology, in line with the long-term vision presented in
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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circuits (PMICs) for sustainable and autonomous sensing systems. The goal of this PhD project is to develop a fully integrated energy-extraction chip that efficiently converts mechanical energy into
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fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production? Information Integrated
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon