Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Nottingham
- Cranfield University
- ; The University of Manchester
- ;
- ; University of Warwick
- AALTO UNIVERSITY
- ; Swansea University
- ; University of Nottingham
- University of Cambridge
- ; Aston University
- ; City St George’s, University of London
- ; Loughborough University
- ; St George's, University of London
- ; University of Cambridge
- Durham University
- 5 more »
- « less
-
Field
-
A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
-
A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
-
defects without compromising structural integrity, thus ensuring passenger safety and operational efficiency. The project aims to design and prototype a ground-based automated inspection system capable
-
This position is part of an exciting initiative to decarbonise and automate port operations, specifically focusing on the electrification, automation, and predictive maintenance of tugboats. The successful
-
Department/Location: Department of Engineering, Central Cambridge We are seeking a highly motivated Research Assistant/Associate to join EPSRC and industry funded Digital Roads (DR) Prosperity Partnership at the University of Cambridge. This programme is a collaboration between industry and...
-
group have developed an AI-enabled system which can extract detailed retinal vasculometry characteristics from colour fundus photographs (CFPs) in a fully automated way, allowing application to large
-
Solubility, and dissolution dynamics, are key physico-chemical properties of active ingredient solid forms and are required across the chemical industry, however their determination remains a bottleneck in the screening process. This PhD project will address this through deep integration of...
-
methods for defect detection; Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data; Create AI models for automated defect detection, classification, and
-
harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
-
automated rankings. The research includes real-world validation using university admissions data and will contribute to the broader fields of AI in education and ethical decision-making. This PhD research