36 parallel-computing-numerical-methods "Simons Foundation" PhD positions at Cranfield University
Sort by
Refine Your Search
-
trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
-
operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
-
deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of
-
combustion environments. Alternative fuels have a different chemical composition from natural gas, which would change depending on the production method used. These unique compositions would translate
-
. However, inefficiencies in wind turbine control and maintenance lead to increased operational costs and reduced energy output. Traditional maintenance methods rely on reactive or time-based servicing, which
-
validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
-
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
-
-the-loop testing, and advanced AI methods will further enrich the student’s research experience. The student will have the opportunity to join a vibrant community and team of researchers. This project will
-
Rolls-Royce the project will focus on the development and testing of novel ultrasonic methods to measure intake massflow for aero-engines. This technology has the potential to improve the methods
-
systems that continuously assess the health of components, predicting failures before they occur. Compliance Assurance Techniques: Design AI-driven methods to ensure ongoing compliance with industry