Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- European Space Agency
- Delft University of Technology (TU Delft)
- University of Twente (UT)
- Eindhoven University of Technology (TU/e)
- Leiden University
- University of Amsterdam (UvA)
- University of Twente
- Erasmus University Rotterdam
- Tilburg University
- University Medical Center Utrecht (UMC Utrecht)
- Wageningen University & Research
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e); Published yesterday
- Erasmus MC (University Medical Center Rotterdam)
- University of Groningen
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- 8 more »
- « less
-
Field
-
1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable
-
to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
-
bottlenecks in clinical radiology workflows through observations, structured workflow mapping, and close collaboration with clinical staff. Design, develop, and evaluate AI-based and automated workflow
-
algorithms developed for the mission. The aim of this project is to develop and test enhanced L2 algorithms for the four hydrological parameters of HydroGNSS, leveraging a combination of machine learning
-
scheduling to help make offshore wind farms a reality. Job description This post-doctoral position focuses on developing fundamental algorithmic advances for dynamic planning and scheduling in multi-objective
-
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
-
for Mathematics and Computer Science (CWI). QuSoft’s mission is to develop new protocols, algorithms and applications that can be run on small to full-scale prototypes of a quantum computer. QuSoft has over 30 full
-
? Join our innovative project where simulated data and real hardware testing create innovative solutions. The work builds on our recent results . You will be at the forefront of developing advanced
-
where simulated data and real hardware testing create innovative solutions. The work builds on our recent results . You will be at the forefront of developing advanced perception systems, using deep
-
of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and