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Electrical & Electronic Engineering - Structured

Course overview
The Structured PhD is a 4-year programme which offers added value to the core component of doctoral training. Students on this programme are offered disciplinary or dissertation specific modules, as well as generic and transferable skills designed to meet the needs of an employment market that is wider than academia.

The programme is flexible and student centred, as candidates choose their own pathways in consultation with their Supervisor and Graduate Research Committee.

New entrants may register for the programme from September to March each year

The thesis remains central to the award of the PhD and is weighted at 330 ECTs.

Students select appropriate skills modules in consultation with their Supervisor and/or Postgraduate Research Committee as follows: At least 10 ECTs in two of the three skills categories, and an overall total of at least 30 ECTs

Skills Categories:
(i) Problem Based Learning;
(ii) Publication / Dissemination;
(iii) Formal Training (from a range of Discipline-specific, Interdisciplinary and Generic modules).

Entry requirements

PhD—high Honours standard in the primary degree.

Duration

Structured PhD, full-time—1SPE1 (four years duration)

Further enquiries

Ms. Mary Costello, Administrator,
Electrical & electronic Engineering,
NUI Galway
T: +353 91 492 728
E: mary.costello@nuigalway.ie

Application date

Course Code: Structured PhD, full-time—1SPE1 (four years duration) Structured PhD, part-time—1SPE2 (six years duration)

PhD (full-time, four years); applications are made online via the NUI Galway Postgraduate Applications System.

New entrants may register for the programme from September to March each year

The thesis remains central to the award of the PhD and is weighted at 330 ECTs.

Students select appropriate skills modules in consultation with their Supervisor and/or Postgraduate Research Committee as follows: At least 10 ECTs in two of the three skills categories, and an overall total of at least 30 ECTs

Skills Categories: (i) Problem Based Learning; (ii) Publication/Dissemination; (iii) Formal Training (from a range of Discipline-specific, Interdisciplinary and Generic modules)

Research areas

Current research projects–

Car-based detection of pedestrians at night-time using imaging techniques

Treatment of venous leg ulcers using Neuromuscular Electrical Stimulation

Using web technologies and social networking to improve adherence to exercise

Development of a leadless cardiac pacing device

Reconfigurable low power scalable hardware neural network for self repairing system

Research into transport delay in VoIP systems

DSP algorithm for mobile digital health

Advanced biometric recognition and matching techniques
Battery management in renewable energy applications

Research Areas

Biomedical Engineering
Exercise Engineering
Ambient assisted Living
Biomedical Electronics
Rehabilitation Engineering
Cardiovascular Electronics
Medical Imaging
Automotive Electronics
Diagnostic & Therapeutic Engineering for Cancer
Communications
Power Electronics
Energy Conversion
Bio-inspired Electronics
Reconfigurable Computing
Embedded Systems
Web Technologies

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