Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- ; The University of Manchester
- Cranfield University
- Forschungszentrum Jülich
- Vrije Universiteit Brussel
- ; Newcastle University
- ; University of Sheffield
- ; University of Southampton
- Aalborg University
- Leiden University
- Linköping University
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- Newcastle University
- Radboud University
- University of Adelaide
- University of Copenhagen
- University of Nebraska–Lincoln
- University of Oslo
- Uppsala University
- 9 more »
- « less
-
Field
-
monitoring and health monitoring of the different machine components. To this end, multiple dedicated measurement campaigns have been performed throughout the Belgian offshore zone, resulting in a large in
-
perform measurements of AI algorithms to fill in the unknowns uncovered in such a data flow diagram. The energy scalability of the core algorithms of a new nationwide AI system can be predicted using
-
Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science, is looking for a: PhD Candidate, Efficient LLM Algorithm, Hardware and System Design (1.0 FTE) Project description We
-
in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
-
control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
-
physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
-
—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
-
, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain
-
. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
-
integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty