Sort by
Refine Your Search
-
neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform
-
representations, and flow matching) for uncertainty-aware 3D reconstruction of coronary anatomy from 2D X-ray angiography; develop physics-informed neural networks and graph-based neural operators for fast
-
your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
-
, particularly artificial neural networks, and deep learning? And you would like to continue your research on clinically relevant topics? If yes, then Maastricht University has a new challenge for you! Postdoc
-
on developing hybrid traffic flow models that combine physical modelling principles with machine learning approaches, such as Physics-Informed Neural Networks (PINNs) and machine-learning-enhanced traffic models
-
with traffic jams spreading like oil spills over entire networks. We believe traffic management based on reliable predictions is therefore crucial to ensure accessibility and safety, especially during
-
for extraterrestrial deployment, bio-inspired robotics experiments on the International Space Station, and novel neuromorphic and spiking-neural-network concepts for resource-constrained autonomous spacecraft