Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ; Swansea University
- Cranfield University
- ;
- University of Nottingham
- ; The University of Manchester
- University of Cambridge
- ; University of Birmingham
- ; University of Nottingham
- AALTO UNIVERSITY
- ; University of Cambridge
- ; University of Exeter
- ; Brunel University London
- ; Cranfield University
- ; The University of Edinburgh
- ; University of Sheffield
- KINGS COLLEGE LONDON
- UNIVERSITY OF VIENNA
- University of Newcastle
- University of Sheffield
- ; Edge Hill University
- ; Lancaster University
- ; Manchester Metropolitan University
- ; Newcastle University
- ; UWE, Bristol
- ; University of Leeds
- ; University of Strathclyde
- Brunel University
- Manchester Metropolitan University
- Oxford Brookes University
- UNIVERSITY OF SOUTHAMPTON
- University of Bristol
- University of Manchester
- 22 more »
- « less
-
Field
-
access to personal development opportunities (e.g. research communication and entrepreneurship training) and the ability to interact with two spin-out companies Lineat and iCOMAT. The PhD project will
-
compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
-
the Department of Biomedical Engineering at Swansea University, but you will also interact closely with our national network of clinicians from across the UK. This ensures the project stays grounded in clinical
-
simulation study of light matter interaction, digital twin enabled process development and life cycle assessment will be researched. Opens: Immediately Deadline: 08/08/2025. Duration: 36 months Funding: Funded
-
Analyse recorded animal behaviours throughout experimental trials and correlate behavioural variability with neural responses to naturalistic audio-visual stimuli Examine cross-modal interactions between
-
materials interact with the body. This project addresses that gap by engineering a 3D-printed full-thickness skin model that mimics the aging microenvironment, enabling more predictive evaluation of novel
-
in radiation–matter interactions, computational modelling, and materials science, with a strong publication record (h-index 36, i10-index 69). Dr Francesco Fanicchia, Research Area Lead: Material
-
bind to protein ligands via sulphated residues that interact with positively charged regions within the protein ligand(s). The 3D organisation of these domains is therefore critical for their function
-
and studded footwear. It will also provide excellent employment opportunities to the researcher. Aims: (1) to enhance current traction testing methods to better reflect player boot-surface interactions
-
well as ecological interactions. These data will be analysed to understand similarities and differences between disturbed and undisturbed patches to assess resilience. If feasible, measures of resilience will be