Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Manchester
- ; University of Birmingham
- University of Cambridge
- University of Nottingham
- ; University of Sussex
- ; Manchester Metropolitan University
- ; University of Warwick
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; Oxford Brookes University
- ; The University of Manchester
- ; University of Leeds
- ; University of Nottingham
- ; University of Surrey
- AALTO UNIVERSITY
- Abertay University
- Royal College of Art
- 9 more »
- « less
-
Field
-
This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
-
manually and on a case by case basis – a process that is long, tedious, and prone to errors. We can streamline this process, to make it more accessible to users without deep floating-point knowledge. One can
-
adaptive signal processing whose combined performance and resilience can easily exceed that of the sum of their parts. However, fundamental and significant questions to provide their practical feasibility
-
costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
-
-matter Bose-Einstein condensates (BEC) using optical signals in the telecom and infrared (IR) spectral ranges. Project background: The control methods are enabled by strong exciton-photon and exciton
-
performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
-
at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
-
, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
-
of organisation-wide processes such as strategy formulation and human resources with R&D; The relationship between organisation-level activities and performance, and national and regional innovation systems
-
the areas of robotics, or autonomous systems, interested in autonomous systems and signal processing. Keen to work with equipment and embedded platforms. Funding To be eligible for this funding, applicants