Sort by
Refine Your Search
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; University of Nottingham
- ; King's College London
- ; Loughborough University
- ; The University of Manchester
- ; University of Leeds
- University of Warwick
- ; Anglia Ruskin University
- ; Aston University
- ; Austrian Academy of Sciences
- ; Cranfield University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Swansea University
- ; UWE, Bristol
- ; University of Birmingham
- ; University of Bristol
- ; University of Essex
- ; University of Exeter
- ; University of Reading
- ; University of Southampton
- ; University of Surrey
- ; University of Warwick
- ; University of York
- Abertay University
- University of Liverpool
- 17 more »
- « less
-
Field
-
limiting their ability to perform essential daily tasks. This interdisciplinary PhD project aims to design a new generation of soft exoskeletons using smart textiles, driven by artificial intelligence (AI
-
) intercultural research on diversity in professional contexts, and ii) linguistic bias in Large Language Model Artificial Intelligence. Eligibility: Home fee paying students. Applicants must have submitted
-
for individuals with a strong interest in artificial intelligence, machine learning, process systems engineering, and pharmaceutical manufacturing. The expected outcomes will contribute to more resilient
-
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
-
and operations; integrated air and missile defence; information advantage and future aerospace combat power; artificial intelligence) may be taken into account when evaluating an application
-
Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
-
predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
-
AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
-
Manufacturing process for Cold Spray with Artificial Intelligence, operate the AM machine, characterise the materials with scanning electron microscopy and transmission electron microscopy with tensile testing