Course

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Master of Applied Neuromorphic Engineering

Approved Abbreviation: MAppNeuroEng

Western Sydney University Course Code: 8124.1

AQF Level: 9

CRICOS Code: 106434D

This version applies to students whose commencement year for this program is 2022 or later. Please use the link to the new Handbook for details.

https://hbook.westernsydney.edu.au/programs/master-applied-neuromorphic-engineering/

Neuromorphic Engineering is an exciting inter-disciplinary field combining aspects from electrical engineering, computer science, neuroscience, signal processing and mathematics. The Master of Neuromorphic Engineering offers students an opportunity to partner with high-profile industry partners in an applied project or a research project, mentored by leading researchers from the International Centre for Neuromorphic Systems at the MARCS Institute. This course seeks to address the rapidly growing demand for alternative inter-disciplinary technologies, such as bio-inspired agile sensory systems, smart edge devices, and brain-inspired high performance computational platforms. The students will be introduced to state-of-the-art neuromorphic hardware, sensors and algorithms in a highly structured way that increases their acumen for approaching new situations with creativity and initiative.

All students will enrol in the 8124 Master of Applied Neuromorphic Engineering and have the option to transition to 8123 Master of Neuromorphic Engineering at the end of their first year. A student completing the two-year degree may apply to pursue a PhD. Two exit options (Graduate Certificate in Neuromorphic Engineering and Graduate Diploma in Neuromorphic Engineering) are also available.

The majority of the coursework units will be undertaken at Parramatta City - Hassall St campus, while the applied project and research project will be located at Penrith campus.

Study Mode
One and a half years full-time or three years part-time. Students may be required to travel between campuses to complete their units.

Admission

Admission to the course requires

An undergraduate degree in electrical, electronics, or biomedical engineering or computer science; and

A one page statement of purpose showcasing solid achievements behind you that show promise for your success in graduate study.

Be selected by interview from the International Centre for Neuromorphic Systems (ICNS) within The MARCS Institute.

Applicants who meet the academic requirement will be invited to an interview to discuss previous experience and suitability for the course.

Course Structure

Qualification for this award requires the successful completion of 120 credit points as per the recommended structure below.

Recommended Sequence

Full-time

Year 1

Autumn session

800229

Neuromorphic Electronics Design

301440

Mathematics of Signal Processing

401471

Introduction to Neuroscience

301493

Programming for Data Science

Students may exit with a Graduate Certificate in Neuromorphic Engineering at this point.

8126 - Graduate Certificate in Neuromorphic Engineering

Spring session

800231

Neuromorphic Accelerators

800232

Neuromorphic Algorithms and Computation

800233

Neuromorphic Sensing

301119

Advanced Machine Learning

Students may exit with a Graduate Diploma in Neuromorphic Engineering at this point.

8125 - Graduate Diploma in Neuromorphic Engineering

Year 2

800235

Applied Project in Neuromorphic Engineering

Note: Students who have met minimum 6.0 GPA requirements for 8123 Master of Neuromorphic Engineering will be able to transfer to this course and complete the unit 800234 Master Dissertation in Neuromorphic Engineering (80 credit points) instead of unit 800235 Applied Project in Neuromorphic Engineering (40 credit points).