Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- Loughborough University
- University of Birmingham
- University of Nottingham
- University of East Anglia
- ;
- Imperial College London;
- The University of Manchester
- University of Exeter
- University of Sheffield
- University of Warwick;
- Imperial College London
- KINGS COLLEGE LONDON
- King's College London
- Kingston University
- Newcastle University
- Oxford Brookes University
- Swansea University
- University of Birmingham;
- University of Cambridge;
- University of Exeter;
- University of Hull
- University of Hull;
- University of Oxford
- University of Oxford;
- University of Surrey
- University of Warwick
- 17 more »
- « less
-
Field
-
This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
-
Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
developed a dataset by conducting high-velocity impact experiments on CFRP specimens using controlled testing setups. The multimodal dataset is to be processed using X-ray CT scans, SEM imaging, and
-
as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
-
This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
-
, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
-
Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This project is a collaborative research effort between
-
focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
-
some of the biggest challenges in medicine today? Join us to explore groundbreaking science that could revolutionize how we treat inflammation-driven age-related diseases and promote healthier ageing
-
data-driven approaches, multi-scale model development and software development depending on the interest of the successful applicant. Big picture: The Tarzia Research Group (https