Funded PhD Opportunity Exploiting Brain Information Processing in Hardware to Develop Highly Reliable, Always-on Smart Sensor Systems.
This opportunity is now closed.
Subject: Computer Science and Informatics
Sensor systems need to be able to sustain operation long periods of time (years) and be reliable in harsh and often remote environments, e.g. bridges, deep in forests, along vast border areas .
This PhD project will innovate in engineering a ‘smart’ sensor system which is highly reliable in facilitating an intelligent ‘always-on’ sensing capability; it will enable a new generation of smart always-sensing systems. The project aims to:
(1) demonstrate the autonomous detection and prediction of events e.g. environment/structure anomalies, using leading edge brain-inspired computational algorithms such as astrocyte-neuron networks  and
(2) demonstrate high reliability capabilities of the computational algorithms in FPGA hardware .
Therefore, the aim is to develop a highly novel system architecture that is ‘smart’ in processing sensory information, and self-adaptable to errors/faults over long time scales (years). Fundamentally, the research aims to prototype a smart sensor system, which integrates a novel, neural FPGA-based processor with existing sensors. The core objectives are defined as:
1. Investigate an astrocyte-neuron network (smart algorithm) which performs detection and prediction of environment/structure anomalies.
2. Benchmark the ‘smart’ algorithm performance against traditional approaches [4-6].
3. Use existing hardware blocks  to implement the smart algorithm in FPGAs.
4. Develop an FPGA hardware demonstrator of always-on smart sensor system, evaluate it and benchmark hardware reliability.
The successful student will be located at the Intelligent Systems Research Centre on the Magee campus of the Ulster University.
The anticipated outcome of the project will be a new scalable solution to self-repair in future computing systems. A highly novel self-repairing embedded hardware architecture will be developed with wide impact on the Electronic Systems research community. Also, several published conference and journal papers on the performance of the proposed mechanisms.
Resources Access to modern Altera FPGAs and a large suite of Agilent logic analyser/oscilloscope instrumentation; existing in-house FPGA-based astrocyte-neurons  available; data and tools on astrocyte-neuron network modelling; and access to real-world sensor data from forest fires.
- Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)
- Experience using research methods or other approaches relevant to the subject domain
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
- First Class Honours (1st) Degree
- Masters at 70%
- For VCRS Awards, Masters at 75%
- Publications - peer-reviewed
Vice Chancellors Research Scholarships (VCRS)
The scholarships will cover tuition fees and a maintenance award of £15,009 per annum for three years (subject to satisfactory academic performance). Applications are invited from UK, European Union and overseas students.
The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,009 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided). For Non EU nationals the candidate must be "settled" in the UK.
- Computing, Engineering and the Built Environment
- School of Computing, Engineering and Intelligent Systems
The Doctoral College at Ulster University
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