Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Exeter;
- University of East Anglia
- University of Exeter
- University of Birmingham;
- Imperial College London;
- The University of Edinburgh;
- The University of Manchester
- The University of Manchester;
- University of Birmingham
- University of Cambridge;
- University of Nottingham
- KINGS COLLEGE LONDON
- Loughborough University
- Swansea University;
- University of Bristol
- University of Plymouth
- ;
- Newcastle University
- Newcastle University;
- Swansea University
- UNIVERSITY OF VIENNA
- University of Newcastle
- University of Oxford;
- University of Surrey
- University of Warwick
- Cranfield University;
- Edinburgh Napier University;
- European Magnetism Association EMA
- Imperial College London
- King's College London
- King's College London Department of Engineering
- Loughborough University;
- Oxford Brookes University
- The Medicines And Healthcare Products Regulatory Agency;
- The University of Edinburgh
- UCL
- UCL;
- University of Bristol;
- University of Cambridge
- University of East Anglia;
- University of Hull
- University of Kent;
- University of Leeds
- University of Oxford
- University of Surrey;
- University of Warwick;
- 37 more »
- « less
-
Field
-
mission. You will: Help collate data resources relevant to suicide and self-harm. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and
-
data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
-
provide large and complex datasets. By applying advanced pattern recognition and clustering algorithms, the aim is to automatically detect coherent spatial domains. These domains represent regions with
-
) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
-
to apply and secure funding through other studentships. I will also be recruiting a postdoc in the similar research space soon, in case you know researchers who may be interested in applying.
-
approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
-
To combat climate change and achieve the UK's target of Net Zero, it is expected that the integration of renewable energy sources (RESs) at the distribution/consumption level will keep increasing
-
having been used by humans and integrated the data with a global bivalve database of species traits, fossil occurrences and geographic distributions, setting the foundation for a forecasting framework
-
Researcher will influence the direction of application areas and algorithm development, receiving direct training in InSAR processing, geospatial data science, and agricultural remote sensing. Co-supervision
-
Museums and Inclusive Heritage Preservation Platform Labour, Creator Economies, and Algorithmic Change AI in the Creative Industries (cross-faculty potential) Independent Cinema Exhibition and UK Screen