Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Twente
- Delft University of Technology (TU Delft)
- University of Amsterdam (UvA)
- Eindhoven University of Technology (TU/e)
- University of Twente (UT)
- Utrecht University
- Wageningen University & Research
- KNAW
- Leiden University
- Maastricht University (UM)
- Vrije Universiteit Amsterdam (VU)
- Delft University of Technology
- Erasmus University Rotterdam
- Radboud University
- University Medical Center Utrecht (UMC Utrecht)
- University Medical Centre Groningen (UMCG)
- University of Groningen
- Wetsus - European centre of excellence for sustainable water technology
- 8 more »
- « less
-
Field
-
organizational environments in which they operate? Addressing these questions requires ethnographic inquiry that considers not only the technical elements of GenAI but also their organizational implications
-
component descriptions, and how these components can be interconnected. We are looking for a candidate with strong programming skills; prior experience in applying and understanding generative AI methods and
-
fundamental component of nearly all wireless transceivers, but existing architectures face increasing challenges in meeting the performance requirements of next-generation systems. This position is part of
-
travel budget is available. The position comes with a small teaching component (at most 15% of the contract time) in English (or Dutch if you are proficient in Dutch). If desired, there is the possibility
-
collaborative, data driven, computational and intelligent systems, all with a strong interactive component. You will be part of Amsterdam Machine Learning Lab (AMLab). AMLab conducts research in machine learning
-
Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component
-
nanoparticles, cell survival and radioresistance. The MS-RADAM research programme combines state-of-the-artc omputational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics
-
Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component
-
technical and systemic challenges, such as component redesign for repair, integration of AM into existing production and supply chains, and performance, sustainability or cost trade-offs compared
-
solution for repair and remanufacturing across industrial sectors. The research will address key technical and systemic challenges, such as component redesign for repair, integration of AM into existing