Sort by
Refine Your Search
-
requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
-
ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of
-
Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
-
Join our exciting PhD programme in Security Automation and be at the forefront of changing the way we protect ourselves from cyber threats. In today's ever-evolving digital world, we urgently need
-
funded studentship is part of the Connected Waters Leverhulme Doctoral Programme, which is funding up to 18 PhD studentships to conduct multidisciplinary research on freshwater ecosystems, across two
-
of compressed gas-guns to characterise materials, computational modelling, and microstructural analysis. Facilities across Cranfield’s key sites (Shrivenham, Cranfield and COTEC) would be employed as required
-
This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for...
-
to develop the coagulation process for phosphorus removal from wastewater. This is an experimental program that will explore how the type of phosphorus species and water characteristics influence
-
carried out at Cranfield in the continuity of what is done by considering the new experimental developments. For these CFD studies, numerical tools and super computers at Cranfield and Loughborough will be
-
This PhD project offers a unique opportunity to delve into the complexities of free-market systems and sustainability through a novel ensemble prediction model. With a focus on addressing uncertainty and limited data availability, this research aims to revolutionize decision-making in...