Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ;
- University of Sheffield
- Cranfield University
- Heriot Watt University
- Imperial College London
- AALTO UNIVERSITY
- Durham University
- Loughborough University
- University of Bristol
- University of Glasgow
- University of Newcastle
- ; The University of Manchester
- ; University of Sheffield
- ; University of Warwick
- DURHAM UNIVERSITY
- Glyndwr University
- UNIVERSITY OF SURREY
- Ulster University
- University of Manchester
- University of Nottingham
- University of Stirling
- 11 more »
- « less
-
Field
-
engage in immersive, simulated construction tasks, while wearable sensors monitor their physical effort, emotional states, and cognitive load. Physiological and behavioural data — including eye tracking
-
transmission methods (wired or wireless) will be optimised for robust data capture in natural sleep environments. AI-Driven Analysis: Develop advanced AI algorithms to analyse the collected sensor data, aiming
-
The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
-
-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble
-
sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
-
of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of tasks. Through this, we aim to develop a framework that can automatically
-
field (a PhD is essential for the Research Associate position), experience working with wearable sensor data and digital outcomes; proficient and independent signal processing and coding, statistical and
-
-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
-
, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
-
—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient