Sort by
Refine Your Search
-
Listed
-
Employer
- Cranfield University
- Imperial College London;
- Loughborough University
- University of East Anglia
- University of Birmingham
- University of Birmingham;
- University of Exeter
- University of Nottingham
- University of Sheffield
- ;
- Coventry University Group;
- European Magnetism Association EMA
- Loughborough University;
- Manchester Metropolitan University
- Manchester Metropolitan University;
- Oxford Brookes University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Cambridge
- University of East Anglia;
- University of Exeter;
- University of Hull
- University of Oxford;
- University of Warwick
- University of Warwick;
- 14 more »
- « less
-
Field
-
into the generation process. This multidisciplinary project will deliver deployable models, reproducible methods, and, where allowed, shareable datasets. The student will gain training in deep learning, AI, image
-
this project unique? You will use cells isolated from human blood and innovative in vivo models in zebrafish to dive deep into the exciting world of RNA biology and immunology, exploring how ELAVL1 regulates
-
deep learning environments (e.g. pytorch) or a computer systems background CDT studentships The CDT has a minimum of 10 fully-funded studentships available for September 2026 entry. Studentships include
-
the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
-
designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
-
on the performance of the CMF; Using machine-learning (deep learning) methods to develop a predictive model and conduct the sensitivity study to investigate the multiple factors on the performance of flow meter
-
on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques
-
), computation (bioinformatics, machine learning, statistical analysis), working with animals (radio-tracking, animal handling/sampling), and deep knowledge of evolutionary biology and gerontology. The Norwich
-
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
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine