Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- University of East Anglia
- University of East Anglia;
- Newcastle University
- ;
- The University of Manchester
- University of Cambridge
- AALTO UNIVERSITY
- University of Birmingham
- University of Nottingham
- University of Sheffield
- Imperial College London;
- Loughborough University
- The University of Manchester;
- University of Cambridge;
- University of Newcastle
- King's College London
- Loughborough University;
- University of Essex
- Bangor University
- Swansea University
- The Institute of Cancer Research
- University of Exeter;
- University of Leeds;
- University of Oxford
- University of Plymouth;
- ; University of Exeter
- European Magnetism Association EMA
- King's College London Department of Engineering
- Manchester Metropolitan University;
- Nature Careers
- Newcastle University;
- Oxford Brookes University
- Royal Holloway, University of London;
- Swansea University;
- UNIVERSITY OF VIENNA
- University of Birmingham;
- University of Bradford;
- University of Leeds
- University of Liverpool
- University of Manchester
- University of Oxford;
- University of Reading;
- University of Surrey
- University of Warwick
- 35 more »
- « less
-
Field
-
change impacts. Research methodology You will integrate multi-platform datasets from ship surveys and oceanic moorings, combining net-derived plankton data with image-based observations to investigate
-
inaccurate for most scientific applications. To harness these accelerators for scientific computing, one must develop new algorithms that combine low and high precision computations in a way that preserves
-
synthesis and in vitro translation of non-canonical amino acids (ncAAs) for expanding the chemical functionality of proteins.[1-5] This project combines organic synthesis, chemical biology and in vitro
-
databases. Integrating image- and text-derived datasets poses challenges due to differences in scale, structure, and accuracy, requiring robust data fusion and validation. By combining these AI-derived trait
-
oscillators interacting with body geometry and environment, rather than from centralized digital control. Using a combination of reduced-order models (Hopf/van der Pol/Kuramoto type) and experimental
-
microclimates that demand dense sensor networks and reliable data retrieval. This project focuses on developing nature-inspired hardware to deploy Internet of Things (IoT) sensors in forest ecosystems. Combining
-
supervised by Professor Dan Parsons, Professor Dapeng Yu (Loughborough and Previsico), Dr Quan Le (Loughborough) and Dr Chris Hackney (Newcastle). Working within the FLOOD-CDT, you’ll combine satellite remote
-
structures. This highly interdisciplinary project combines mechanical engineering, materials science, and control systems, and will require both numerical simulation and experimental validation. The outcomes
-
to revolutionise nanotechnology by combining organic chemistry and polymer science to create materials that respond and adapt to their surroundings. This PhD project focuses on Ostwald ripening, a fundamental
-
learning) to combine datasets and preserve extremes. Uncertainty will be quantified explicitly, with outputs designed to inform both researchers and practitioners. The resulting dataset, open-access and user