87 algorithm-"Multiple"-"U"-"Prof"-"Simons-Foundation" "University of South Eastern Norway" PhD positions in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Nottingham
- ; Newcastle University
- ; Swansea University
- ; Edge Hill University
- ; University of Birmingham
- ; University of Exeter
- ; University of Leeds
- ; The University of Edinburgh
- ; University of Bristol
- ; University of Cambridge
- ; University of Southampton
- University of Cambridge
- ; Cranfield University
- ; Lancaster University
- ; University of East Anglia
- ; University of Nottingham
- ; University of Oxford
- ; University of Sheffield
- ; University of Surrey
- Imperial College London
- University of Newcastle
- 14 more »
- « less
-
Field
-
sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
-
-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
-
developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
-
of advanced computational techniques. This research will integrate power system modelling, optimisation algorithms, and artificial intelligence (AI) techniques to develop an innovative framework for strategic
-
—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
-
leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
-
areas, and be able to creatively combine disciplines to make new research advances in fluid mechanics. You will be creating data-driven algorithms which can solve state estimation problems in fluid
-
formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
-
-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
-
powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy