Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Manchester
- Cranfield University
- ;
- AALTO UNIVERSITY
- Loughborough University
- Swansea University
- Loughborough University;
- University of East Anglia
- Harper Adams University
- University of East Anglia;
- Newcastle University
- The University of Edinburgh;
- University of Cambridge
- University of Exeter
- University of Nottingham
- The University of Edinburgh
- University of Birmingham
- University of Bristol;
- University of Glasgow
- University of Liverpool
- University of Reading;
- Bangor University;
- City St George’s, University of London
- Imperial College London
- Newcastle University;
- The Open University;
- Trinity Laban Conservatoire of Music and Dance
- University of Bristol
- University of Derby
- University of Glasgow;
- University of Greenwich;
- University of Hertfordshire
- University of London
- University of Newcastle
- University of Oxford
- University of Plymouth
- University of Plymouth;
- University of Reading
- University of Sheffield
- University of Warwick
- 30 more »
- « less
-
Field
-
candidate will enjoy working on finite-element based modelling, the application of mathematical concepts from UQ/ML to practical problems, and an understanding of scripting/programming. Individuals with
-
of Nottingham, but should expect to engage fully with the 3-month full-time training programme in the Fusion Engineering CDT at the start of the course (October to December inclusive). CDT training will be
-
at speed to ensure efficacy and compliance of food fortification programs in low- and middle-income countries (LMICs). The successful applicant will lead the electronic and digital engineering of the eLFA
-
at the 2026/27 UKRI rate) (note that the 2025/26 rate is £20,780), and a research training support grant of £20,000. Overview This PhD project is part of the EPSRC Centre for Doctoral Training in Process
-
improvements in machine learning (ML) applications now allow researchers without extensive programming backgrounds to implement advanced image-processing techniques using accessible programming languages and
-
frameworks. This approach is timely, as improvements in machine learning (ML) applications now allow researchers without extensive programming backgrounds to implement advanced image-processing techniques
-
programming skills (Python, MATLAB), excellent communication and ability to integrate numerical modelling, sensor technologies, and occupant-focused design. Experience in thermodynamics, building physics
-
teaching assistantship. The ideal candidate will have a strong foundation in Python programming and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch. Applicants with a
-
professional networks. Candidate’s profile Knowledge of quantum computing and an understanding of challenges of building large-scale systems Programming skills in Python A good Bachelor’s Hons degree (2.1
-
for a Programme , create your account and use the link sent by email to start the application process. Please select the PhD in Archaeology. *Important notes* 1) Please quote the reference ‘DRC25-137’ in