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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
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- 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
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should have an intrinsic interest for marketing problems. The PhD will be supervised by Prof. Dr. Lemmens and funded by a VICI NWO grant. Keywords Algorithmic bias, Causal Inference, Discrimination
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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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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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, the scattering geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms
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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
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geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer metrology
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non