Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Sheffield
- ; The University of Manchester
- The University of Manchester
- University of Birmingham
- University of Bristol
- University of Cambridge
- University of Nottingham
- ; Swansea University
- ; University of Exeter
- AALTO UNIVERSITY
- UNIVERSITY OF VIENNA
- University of Cambridge;
- ;
- ; City St George’s, University of London
- ; The University of Edinburgh
- KINGS COLLEGE LONDON
- The University of Edinburgh
- University of Glasgow
- University of Warwick
- ; Aston University
- ; Coventry University Group
- ; Imperial College London
- ; Loughborough University
- ; Newcastle University
- ; UCL
- ; University of Birmingham
- ; University of Bristol
- ; University of Cambridge
- ; University of Nottingham
- ; University of Sheffield
- ; University of Southampton
- ; University of Warwick
- Brunel University London
- Lancaster University;
- Liverpool John Moores University
- Newcastle University
- Royal Holloway, University of London
- The University of Edinburgh;
- The University of Manchester;
- UCL
- University of London
- University of Manchester
- University of Newcastle
- University of Nottingham;
- 35 more »
- « less
-
Field
-
The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence will inform future race strategy and live race tactics. Multiple factors influence the strategy...
-
degree or a master’s (or international equivalent) in a relevant science, mathematics or engineering related discipline. Excellence in computational science and mathematics Programming skills in any
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
-
candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
-
(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment
-
This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid
-
Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics