Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; University of Warwick
- ; University of Nottingham
- University of Nottingham
- ; The University of Manchester
- ; University of Exeter
- ; University of Leeds
- ; University of Oxford
- ; University of Reading
- ; University of Surrey
- Imperial College London
- University of Cambridge
- ; Anglia Ruskin University
- ; Austrian Academy of Sciences
- ; City St George’s, University of London
- ; Cranfield University
- ; Durham University
- ; Loughborough University
- ; Newcastle University
- ; Queen Mary University of London
- ; Swansea University
- ; UWE, Bristol
- ; University of Birmingham
- ; University of Bristol
- ; University of East Anglia
- ; University of Greenwich
- ; University of Sheffield
- ; University of Southampton
- ; University of Strathclyde
- ; University of Sussex
- Newcastle University
- University of Birmingham
- University of Glasgow
- University of Newcastle
- University of Sheffield
- 26 more »
- « less
-
Field
-
, structure search and machine-learning, you will tackle the challenge of creating interatomic models that are capable of accurately predicting thermodynamical properties. This is crucial to gain insight and
-
cerium-rich alloys to delocalise and join the valence electrons triggering a dramatic change in properties. The project will explore building machine learning interatomic potentials for further modelling
-
experimentation and validation, and machine learning. References of our current/recent work are here: "Automatic Retrieval-Augmented Generation of 6G Network Specifications for Use Cases," IEEE Communications
-
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
-
(for examples, see https://doi.org/10.1073/pnas.2006192117 ). You will use a variety of analytical methods including principal components analysis and machine-learning to model the covariation of the face, voice
-
algorithms, have excelled in tasks like computer vision, image recognition and large language models (LLM). However, their reliance on extensive computational resources results in excessively high energy
-
Machine Learning-based diagnostics and prognostics digital twin system will be developed, aiming to provide fast and reliable predictions of the health of gas turbine engines. Non-confidential operational
-
degree in a relevant discipline (cognitive neuroscience, neuroscience, computational neuroscience, psychology, cognitive science, machine learning/data science/AI). Start date: 1 October 2025 Funding
-
electron microscopy image simulations Development of a machine learning model capable of inferring 3D atomic structure from two-dimensional TEM projection images Application of the new approach
-
learning models of quantum chemistry can achieve fast and accurate predictions, but comprehensive data sets for reaction barriers of large molecules simply do not exist. Several recent works have attempted