Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; Manchester Metropolitan University
- Manchester Metropolitan University
- ; Cranfield University
- ; Swansea University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Warwick
- Nature Careers
- The University of Manchester
- University of Cambridge
- University of Sheffield
- 3 more »
- « less
-
Field
-
analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall
-
Environment Agency to address crucial gaps in knowledge needed to make nature-based solutions a central strategy for reducing occurrence and impact of SO spills. The objectives of the project include mapping
-
methodology to better understand the safety and performance risks. Finally, multiscale simulations will be used to map learnings from laboratory-based systems (up to10 kW) to predict the behaviour and
-
). You should also complete the Narrative CV form addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being
-
brief standard/narrative CV addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest
-
application form ). You should provide a brief standard/narrative CV addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area
-
the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest. You will need to upload your statement in
-
lived experiences and informing solutions. Phase 1 focuses on quantifying the landscape of oral health inequalities, utilising secondary analysis of large-scale datasets and GIS mapping. Phase 2 explores
-
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
-
and heat transfer in geothermal systems under high-pressure and high-temperature conditions relevant to AGS. • Developing high-fidelity direct numerical simulation (DNS) models to map