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Research Associate - Photonic-Electronic Neuromorphic Systems (791321)

University of Strathclyde - Institute of Photonics

Location: Glasgow
Salary: £37,694 to £46,049 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 4th March 2026
Closes: 8th March 2026
Job Ref: 791321
 

FTE: 1.0

Term: Fixed for 9 months

Applications are sought for a 9-month Post-Doctoral Research Associate (PDRA) position in novel neuromorphic opto-electronic technologies for brain-inspired processing and sensing systems at the edge. The position is based at the Institute of Photonics (IoP, Physics Dept.) at the University of Strathclyde (Glasgow, UK).

The successful candidate will work with Professor Antonio Hurtado, on the EPSRC-funded project ‘Low-Power, High-Speed, Adaptable Processing-In-Sensing (ProSensing)’, a collaborative programme with partners at Edinburgh and Nottingham Trent Univs. The goal of this project is to design, develop and investigate new opto-electronic technologies for low energy, high-speed systems using light signals to perform brain-inspired sensing and in-sensor processing functionalities.

The successful candidate will have access to state-of-the-art photonic labs at Strathclyde. In addition to the design and investigation of neuromorphic optoelectronic systems, the successful candidate will be involved in their experimental characterisation (e.g. speed and energy operation, time analyses) and in the development of training algorithms for their operation in sensing/processing tasks. The applicant will have the opportunity to work with academic partners (Edinburgh and Nottingham Trent Univs) and stakeholders in defence and national security. The appointed researcher will work closely with these partners with the opportunity for research visits and travel to international conferences. The successful candidate will be required to undergo security checks before being employed.
A background in photonics, electronics, laser/LED systems, experimental analysis of optical/opto-electronic devices/systems, and/or neuromorphic sensing/computing technologies is desirable. A background in the programming and algorithm development for the training of neuromorphic (opto-electronic) systems and neural networks is also desirable.

Our research team, with expertise in basic and applied research in neuromorphic photonics, brain-inspired computing, light-enabled AI and nanophotonics, are a collegiate and welcoming group and we are looking for a candidate who will enjoy working in the dynamic environment at the IoP. We look forward to hearing from candidates with good experimental and algorithmic development background and strong oral and written communication skills. Candidates should have an academic or industrial R&D record in photonics or (opto-)electronics and a demonstrable ability to work both collaboratively and independently.

Institutional training courses in leadership skills are available and the successful candidate will be encouraged to undertake these to further their own career objectives. An ability to communicate research effectively is important and public communication training will also be provided.

Whilst not essential for the role, applications are welcomed from candidates with: relevant work experience, membership of relevant Chartered/professional bodies (including the Higher Education Academy), experience of relevant student supervision and teaching activities, and/or experience of knowledge exchange related activities.

Whilst a Post-Doctoral Research Associate is ideally sought for this position; applications from candidates who are close to PhD completion or whose award is pending, are welcome. In such circumstances, the appointment will be made at Research Assistant level (grade 6) and duties will be adjusted to reflect the grade of the post. This will continue until the PhD award is confirmed, at which point the duties and grade will be revised accordingly

The Hurtado group places the highest importance on equality, diversity and inclusion. 

Informal enquiries about the post can be directed to Professor Antonio Hurtado, UKRI Turing AI Fellow (antonio.hurtado@strath.ac.uk).

Click here for full details.

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