Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Newcastle University
- ; Swansea University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Leeds
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- AALTO UNIVERSITY
- University of Newcastle
- ; Imperial College London
- ; University of Exeter
- ; University of Nottingham
- ; University of Plymouth
- ; University of Reading
- Harper Adams University
- 10 more »
- « less
-
Field
-
the development of system software. Key questions include how LLMs can support programmers in writing complex logical code, generating high-quality tests, and optimizing performance. Moreover, when integrated with
-
engines. The variable rotation speeds, complex loading and operating conditions cause significant blade vibrations. These vibrations, if not properly controlled and reduced, can lead to premature blade
-
-electronic and quantum technologies. What you would be doing: Experimental Design and Execution: Plan, conduct and optimize advanced 4D STEM experiments at cryogenic temperatures. This includes working with
-
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
-
frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
-
sensing, and Electromyography (EMG) tools to understand user-device interaction and optimize real-world rehabilitation performance. The student will gain experience in AI, human biomechanics, smart textiles
-
; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 21 days ago
? This PhD, working with Prof. Marcelle McManus , provides an opportunity to work to explore and advance novel decarbonisation solutions for high-energy use industrial sites. Your project will be co-created
-
modelling tools (CST or HFSS) - Fabricate and test for optimal electromagnetic performance, such as bandwidth, return loss, insertion loss and power-handling. - Develop and characterize new bonding/alignment
-
during their PhD studies. Concrete-filled double skin steel tubular (CFDST) sections offer superior structural performance for wind turbine towers due to their enhanced strength, ductility, and material
-
become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address