Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- University of Manchester
- University of Cambridge
- ; University of Birmingham
- ; Swansea University
- ; The University of Manchester
- ; University of Surrey
- ; City St George’s, University of London
- ; University of Exeter
- ; University of Nottingham
- ; University of Southampton
- ; University of Warwick
- AALTO UNIVERSITY
- University of Exeter
- University of Liverpool
- University of Newcastle
- ; Coventry University Group
- ; Edge Hill University
- ; Imperial College London
- ; Manchester Metropolitan University
- ; Newcastle University
- ; University of Cambridge
- ; University of Greenwich
- ; University of Hull
- ; University of Leeds
- Coventry University Group
- Heriot Watt University
- Imperial College London
- The University of Manchester
- University of Bristol
- University of Cambridge;
- University of Nottingham;
- University of Plymouth
- University of Sheffield
- University of Warwick
- 27 more »
- « less
-
Field
-
This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
-
recruitment practices and throughout the delivery of our PhD programme. For 2025 recruitment, we are operating a Guaranteed Interview Scheme for applicants from Black and Black mixed backgrounds. How to apply
-
interviews to assess health behaviours. Experience in a variety of qualitative analysis techniques such as thematic analysis and Interpretative Phenomenological Analysis (IPA), in addition to other mixed
-
recruitment practices and throughout the delivery of our PhD programme. For 2025 recruitment, we are operating a Guaranteed Interview Scheme for applicants from Black and Black mixed backgrounds. How to apply
-
at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
-
, allowing them to add to their existing clinical targets of anxiety and depression disorders, thus developing impact from this research. Methodology This studentship will take a mixed-methods approach to
-
challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
-
mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
-
management—are encouraged to apply. Methodological approaches are flexible and may include qualitative, quantitative, or mixed methods, depending on the research focus. Exemplary research topics include (but
-
analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how