Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- ;
- ; Swansea University
- ; The University of Manchester
- University of Nottingham
- University of Cambridge
- ; Cranfield University
- ; University of Birmingham
- ; University of Bristol
- ; University of Oxford
- AALTO UNIVERSITY
- University of Sheffield
- ; Brunel University London
- ; The University of Edinburgh
- ; University of Surrey
- ; City St George’s, University of London
- ; University of Cambridge
- ; University of Sheffield
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- Abertay University
- Imperial College London
- University of Newcastle
- ; Aston University
- ; Bangor University
- ; Durham University
- ; Loughborough University
- ; Manchester Metropolitan University
- ; Newcastle University
- ; University of Greenwich
- ; University of Nottingham
- ; University of Strathclyde
- ; University of York
- Aston University
- UNIVERSITY OF SOUTHAMPTON
- University of Manchester
- Utrecht University
- 28 more »
- « less
-
Field
-
, there is no consensus on the adsorption mechanisms of these molecules on the metallic surfaces. In this PhD project we will use state-of-art molecular simulation methods [2,3] to clarify the adsorption and
-
Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
-
bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
-
of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo
-
This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
-
heavier than their fossil fuel powered counterparts. A framework that can accurately model complex dynamics and generate projections for future scenarios is essential for understanding the impact of changes
-
scope to tailor the PhD project to your interests and strengths. You will be part of a team researching the complexity and inequalities of transnational (pre-)retirement trajectories across three
-
(or be close to obtaining) a PhD. Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will initially be appointed as a Research
-
, curious individual to join an exciting PhD. This opportunity is generously funded by John Crane Ltd, a world-renowned engineering technology leader. Why This PhD? Impact Clean Energy's Future: Develop next
-
supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system