61 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" PhD positions at Newcastle University
Sort by
Refine Your Search
-
, publications and certification-related artefacts. Supervision Environment You will be based in Newcastle University’s Computing AMBER-group, focusing on safety-critical software, medical systems, simulation, and
-
the most energy‐intensive infrastructures in modern economies, with their demand projected to rise sharply as digitalisation, artificial intelligence (AI), and cloud computing expand. This growth presents
-
prior to obtaining their visa and to study on this programme. How To Apply You must apply through the University’s Apply to Newcastle Portal Once registered select ‘Create a Postgraduate Application’. Use
-
systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots
-
to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload this with your application. Applications which do not include
-
the opportunity to undertake a placement within Scottish Power as part of your program. The project Power Electronic Devices (PEDs) have been proposed as a new approach to increase the uptake of low-carbon
-
-generation regenerative materials. This interdisciplinary project combines mechanical, materials, and biomedical engineering, offering training across fabrication, nanomechanical analysis, and computational
-
on this programme. How To Apply Please read and complete this document as your Personal statement, and upload this with your application. Applications which do not include this document will not be
-
Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload
-
industrial practice relies heavily on empirical optimisation, leading to inefficiencies in energy use and impurity removal. This PhD project proposes to develop a Coupled Computational Fluid Dynamics-Discrete