Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Cambridge
- University of Nottingham
- ; University of Leeds
- ; Manchester Metropolitan University
- ; Newcastle University
- ; University of Birmingham
- ; University of Nottingham
- ; University of Surrey
- ; University of Warwick
- Imperial College London
- ; Anglia Ruskin University
- ; Aston University
- ; Cranfield University
- ; Lancaster University
- ; UWE, Bristol
- ; University of Bristol
- ; University of East Anglia
- ; University of Essex
- ; University of Southampton
- ; University of York
- Harper Adams University
- Newcastle University
- University of Newcastle
- 16 more »
- « less
-
Field
-
-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
-
, stress markers, EEG, and ECG — will be collected by VR headsets and IoT devices. ML algorithms will analyse this data to identify trends, project risk factors, and propose tailored treatments. By combining
-
Engineering (PhD) Eligibility: UK Students Award value: Home fees and tax-free stipend £20,780 - See advert for details Project Title: Machine Learning and Optimisation-Based Intelligent Substation Design in
-
This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
-
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
-
for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
-
In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and
-
In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and
-
aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
-
replacement) project on Limits of Symmetric Computation. The position would suit a candidate seeking to obtain a PhD at the Department. The project seeks to investigate lower bounds on symmetric computation in