Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Delft University of Technology (TU Delft)
- University of Amsterdam (UvA)
- Eindhoven University of Technology (TU/e)
- Wageningen University & Research
- Amsterdam UMC
- Radboud University
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- Centrum Wiskunde en Informatica (CWI)
- Leiden University
- Maastricht University (UM)
- Tilburg University
- University of Groningen
- ARCNL
- Erasmus MC (University Medical Center Rotterdam)
- Radboud University Medical Center (Radboudumc)
- Sanquin Blood Supply Foundation (Sanquin)
- The Open Universiteit (OU)
- University Medical Center Groningen
- University Medical Centre Groningen (UMCG)
- University of Twente (UT)
- 11 more »
- « less
-
Field
-
people represent environments through concepts such as mental models, cognitive maps, and cognitive graphs. These approaches have provided important insights into how people perceive locations, learn route
-
. Learn more about your project at the Model-Driven Decisions Lab . Job requirements You hold an MSc in computer science, data science, or another relevant subject such as ethics of AI, with practical
-
is decentralized or only partially observable? Depending on the research direction, you may employ techniques from mathematical modelling, machine learning, uncertainty quantification, distributed
-
6G and beyond. The project combines analytical modelling, system simulation, photonic integrated circuit design, machine learning, and experimental validation using state-of-the-art communication
-
-year research project aimed at advancing our understanding of foot growth and deformities in children with cerebral palsy. In this project, you will develop statistical shape models and finite element
-
with a background in theoretical physics, statistical, soft or biological physics Experience with using inference/machine learning tools and basic programming is a plus As a university, we strive for
-
independently. We value personal development: you will receive training in advanced computational techniques, machine learning, data analysis and scientific communication. You’ll have the opportunity to attend
-
PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
-
design and characterise reconstruction methods—both machine-learning-based and traditional—for the bundles of muons that reach the detectors, and apply them to data and simulations to constrain cosmic-ray
-
generation of experts skilled in the combination of Operation Research and trustworthy Machine Learning. CoRDS goes beyond the state-of-the-art DDO methods by proposing decision support frameworks that combine