time-critical data to support robotics, fire control to background data, saving people in earthquake conditions to military operations in unknown and changeable environment. Such sensor networks have extended their territory to industrial applications, such as energy management, agricultural monitoring, for measuring temperature, sound, pressure, motion, pollutants, for process control and surveillance. Sensor networks will monitor the environment at close range with high special and temporal resolutions and will likely reveal previously unobservable phenomena in the physical world. This project will investigate novel probabilistic methods for extracting knowledge from data and decision making.

Funding Notes

This is a self-funded research project.
We require applicants to have either an undergraduate honours degree (1st) or MSc (Merit or Distinction) in a relevant science or engineering subject from a reputable institution.
Prospective candidates for this project should have an MSc, MMath or MEng in mathematics, statistics, physics, aerospace engineering, signal processing, electrical engineering or a related subject.
Full details of how to apply can be found at the following link:
View Website
Applicants can apply for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive: View Website