Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Newcastle University
- University of East Anglia
- University of Nottingham
- University of Exeter
- University of Cambridge;
- University of Warwick;
- The University of Manchester
- University of Birmingham
- University of Cambridge
- UNIVERSITY OF VIENNA
- University of Warwick
- University of Oxford
- University of Surrey
- AALTO UNIVERSITY
- Manchester Metropolitan University
- Durham University
- Imperial College London
- Newcastle University;
- Abertay University
- Manchester Metropolitan University;
- Oxford Brookes University
- Swansea University
- University of Bath
- University of Newcastle
- University of Plymouth
- University of Sussex
- ;
- Brunel University
- European Research University
- King's College London
- King's College London;
- Royal Holloway, University of London
- The Francis Crick Institute
- University of Bedfordshire
- University of Liverpool
- University of Manchester
- University of Sheffield
- Biology Centre CAS
- City St George's, University of London (Tooting);
- City St George’s, University of London
- Cranfield University
- Heriot Watt University
- London School of Economics and Political Science;
- Northeastern University London
- Swansea University;
- The Rosalind Franklin Institute
- The University of Edinburgh
- The University of Edinburgh;
- UWE, Bristol
- UWE, Bristol;
- University of Bath;
- University of Birmingham;
- University of Bristol
- University of Chichester
- University of Dundee;
- University of East Anglia;
- University of Exeter;
- University of Glasgow
- University of Plymouth;
- University of Reading
- University of Salford
- University of Sheffield;
- University of Strathclyde
- 53 more »
- « less
-
Field
-
and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
-
scanning and measurement, garment fit evaluation, cloth simulation, digital twins, wearable sensing, smart textiles, and AI methods for clothing and body data analysis, to name a few. Applicants from
-
across historical, social science, and data science methods. While this studentship is grounded in historical and archival practice, candidates who wish to engage with quantitative, digital, or comparative
-
be an integral member of the wearables group based at Oxford, led by Aiden Doherty. Our research team has access to world-leading population health data sets with objective wearable sensor measurements
-
tools and available data to analyse the cost-effectiveness of available interventions to reduce infections from a societal perspective. The student will have the freedom to shape the methodological
-
communication and data presentation skills Fluent in English (German is an advantage) Motivated, collaborative, and able to work independently Expectations for successful candidates: The language of the school is
-
these tools within a real-time digital twin framework, steel producers can access rapid, data-driven insights that support optimised process control, reduced reject and downgrade rates, and meaningful
-
This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a
-
for place with the projects across the MRC GW4 BioMed3 Doctoral Landscape Award studentships. There are a total of 18 studentships available across the partnership. This exciting PhD combines big data and
-
knowledge graph from scientific papers and cognitive test questionnaire data, and second, to integrate the graph with transformer-based large language models and causal learning. This offers an explainable