Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Exeter
- University of Birmingham
- ;
- Newcastle University
- University of Cambridge
- University of Nottingham
- Loughborough University
- Loughborough University;
- University of East Anglia
- University of Plymouth
- University of Plymouth;
- University of Sheffield;
- Cranfield University;
- Imperial College London;
- Manchester Metropolitan University;
- The University of Manchester;
- UCL
- University of Birmingham;
- University of Cambridge;
- University of Exeter;
- University of Hull;
- University of Oxford
- University of Oxford;
- University of Sheffield
- University of Surrey;
- University of Warwick
- 17 more »
- « less
-
Field
-
to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
-
(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
-
This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
-
depletion, toxic algae, and pollutants. This natural sensitivity makes them powerful bio-sensors for environmental monitoring, capable of providing early warnings of ecosystem stress. However, harnessing this
-
materials and innovative sensor architectures that maintain stable performance under bending, moisture exposure, and mechanical loading. The envisioned platform will contribute to future responsive biomedical
-
velocity continuity or GNSS-derived velocity estimates. Sensor fusion consistency: aligning pseudorange corrections with complementary sensors, such as inertial navigation systems. Map-based constraints
-
authentication address digital risks, the physical interfaces of CPS (such as sensors and communication links) remain vulnerable and are often overlooked. A system cannot easily distinguish between genuine and
-
PhD Studentship: Nanopore Technology for Rapid and Accurate Measurement of Antibiotic Concentrations
their use in field or point-of-care settings. This project aims to develop portable, nanopore-based sensors for the rapid and accurate quantification of antibiotic concentrations in environmental and clinical
-
multidisciplinary supervisory team spanning engineering, ecology, and environmental science, with access to state-of-the-art laboratories, field sensors, and data-analysis facilities. You will also join Manchester
-
the question ‘how close to failure is the asset?’. By integrating a suite of state-of-the-art sensors and monitoring technologies with data fusion and AI analytics, this research will enable timely