Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- ; University of Warwick
- University of Nottingham
- University of Sheffield
- ; Cranfield University
- ; Loughborough University
- ; University of Birmingham
- ; University of Oxford
- ; University of Sheffield
- ; University of Southampton
- AALTO UNIVERSITY
- University of Cambridge
- ; Swansea University
- ; University of Exeter
- ; Anglia Ruskin University
- ; Brunel University London
- ; Newcastle University
- ; Queen Mary University of London
- ; University of Cambridge
- ; University of Nottingham
- ; University of Plymouth
- ; University of Reading
- ; University of Surrey
- ; University of Sussex
- Newcastle University
- University of Manchester
- University of Newcastle
- 19 more »
- « less
-
Field
-
release on these projects can be found at the following link . This position’s focus is on developing engineered systems and methods to quantify the physical interactions between migrating cancer cells and
-
to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
-
analysed in a standard web browser. HiPIMS computations can be executed on local GPUs or through cloud-based GPU services, empowering users to conduct large-scale fast flood simulations without worrying
-
to support condition-based predictive maintenance for gas turbine engines. Cranfield has developed unique physics-based technologies on gas turbine performance simulations, diagnostics, prognostics and lifing
-
numerical simulations, probabilistic techniques, and AI analytics, earthwork prognoses could be expressed in the form of ‘time-to-failure’ and/or ‘probability of survival’ under extreme weather events. Please
-
in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
-
us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
-
to study corrosion, cracking and mechanical degradation, develop advanced computational models using modern C++ and high-performance computing to simulate material behaviour over a 100+ year timespan. This
-
Join a project that will combine physics, machine learning, and ultrasonics to design new sensors for the digital revolution in industry. Ultra-thin membranes are produced in many high tech
-
and theoretical and computational collaborators. Your experience and ambitions Interest in experimental condensed matter physics – especially in superconductivity and magnetism. Proficiency in searching