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- Delft University of Technology (TU Delft); yesterday published
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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on the mathematical theory enabling these advances, via asymptotic analysis and nonparametric modeling. You will work in the Statistics section at the Delft Institute of Applied Mathematics (DIAM
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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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candidate will gain training in chemical biology, molecular genetics and cell biology, and use physiologically relevant in vitro and in vivo models. The work will be carried out in an interdisciplinary
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positioned at the University of Twente in Enschede, the Netherlands and get introduced into the PhD trajectory and scientific working. You will alongside the developers of UT’s global crop water model ACEA
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you will: Develop a theoretical framework for designing accessible and inclusive infrastructure and wayfinding systems. Develop VR simulators for people with visual, hearing, motor, and cognitive
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. Options model for additional leave, pension, a bicycle or personal training. Moving allowance (subject to conditions). 30% rule for international employees (if applicable). Pension through ABP. Ample
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–specific ways, and their downstream biological effects remain poorly understood. This project tackles this fundamental gap — by building computational models that simulate what goes wrong in the brain, one
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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-edge infrastructures, and emerging AI-driven user applications. Key research directions include: Modeling and profiling of emerging AI-based workloads and data-intensive applications in mobile networks
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introduced into the PhD trajectory and scientific working. You will alongside the developers of UT’s global crop water model ACEA (Mialyk et al. 2024) and improve the model’s ability to provide recurring