Sort by
Refine Your Search
-
Category
-
Employer
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- University of Twente (UT)
- University of Amsterdam (UvA)
- DIFFER
- Tilburg University
- University of Twente
- Utrecht University
- ARCNL
- Erasmus MC (University Medical Center Rotterdam)
- TU Delft
- University of Groningen
- 2 more »
- « less
-
Field
-
Are you passionate about building an entanglement-based quantum internet? In this PhD project, you will design an entanglement source, a routing architecture, protocols, and set up a testbed that
-
Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural
-
fundamental challenges in reliable, resilient, and sustainable connectivity. You will join an international research environment that values scientific excellence, creativity, meaningful collaborations, and
-
Data Science, Safety and Security research units, in collaboration with the Data Science Centre of Excellence of the Netherlands Defence Academy and the Netherlands Forensic Institute. The PhD researcher
-
doctoral network on quantum error correction, as a PhD candidate at TU/e, designing next-generation codes and decoders for real quantum hardware. Information Quantum computers have grown remarkably fast
-
This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing
-
these codes are central to both. Wanna help shape this key technology behind reliable and secure optical communications? Come join us as a PhD student, designing the error-correcting codes behind
-
PhD Position in Generative AI in Health Technology Assessment (HTA) Faculty: Faculty of Science Department: Department of Pharmaceutical Sciences Hours per week: 36 to 40 Application deadline
-
candidates chosen due to its high melting point, good thermal conductivity and low erosion rate. However, transitioning to the long-term timescales and high reliability required for commercial fusion means
-
, these flows remain poorly understood. As a result, even the most basic properties cannot be predicted reliably. For instance, the best available models over- or underestimate the measured pressure drop in a