Sort by
Refine Your Search
-
Listed
-
Employer
- Utrecht University
- Eindhoven University of Technology (TU/e)
- University of Twente (UT)
- Delft University of Technology (TU Delft)
- University of Amsterdam (UvA)
- University of Twente
- Amsterdam UMC
- DIFFER
- Erasmus University Rotterdam
- Leiden University
- Radboud University
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- 3 more »
- « less
-
Field
-
machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
-
in the new Lab42 building at the Amsterdam Science Park. The VIS Lab performs research on deep learning and computer vision, from hyperbolic learning to medical imaging and from NeuroAI to foundation
-
group? Do you enjoy creating complex machines that have never existed before? Do you want to explore physics that nobody else has seen? Maybe you want to join our team as a PhD on our journey
-
quantitative methodological skills in handling detailed spatial data, including various econometric techniques and machine learning approaches; a thorough understanding of empirical, explanatory research; a
-
, particularly integer programming, e.g., vehicle routing and packing problems and heuristics; simulation; data-driven modelling; decision support systems; AI (reinforcement learning, machine learning). Motivation
-
from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
-
Description This PhD position explores how AI agents can play games to generate meaningful gameplay data. You will work on reinforcement learning, automated feature engineering, and the comparison of AI- and
-
bringing together a diverse team of PhD candidates who will focus on three key areas: Probabilistic and differentiable algorithms for machine learning; Programming language implementation for high
-
fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge
-
, neuroimaging and clinical psychiatry, with direct clinical impact. Your main activities are: analyzing and integrating multimodal MRI data for biotype identification; applying machine learning and advanced