Reservoir Computing (RC) as an enabling technology for robust, lightweight, real-time intelligent systems (resulting in Autonomous Decision-Making)

Summary

This exciting PhD opportunity offers the chance to work at the intersection of neuroscience, cognitive science, and artificial intelligence (AI) to better understand and utilise intelligence in biological brains and in machines.

While cognitive and brain sciences have generated vast amounts of rich, complex data, unlocking their insights requires cutting-edge AI and machine learning (ML) techniques. Meanwhile, although artificial neural networks (ANNs) have powered recent AI breakthroughs, they still fall short in many respects — and the next leap forward may come from studying how biological brains function.

This exciting nexus has been termed NeuroAI. In particular, this PhD project, which is a collaboration between the NeuroAI and Neurotechnology Research Team at Ulster University and Thales UK Ltd., will focus on designing novel AI algorithms inspired by brain functions, to enhance machine intelligence capabilities for real-world applications.

The proposed PhD project on reservoir computing will investigate novel methods for robust, lightweight, and real-time intelligent processing in edge and resource-constrained systems. The research will provide a potential pathway for translating advances in reservoir computing into practical applications in autonomous decision-making.

The primary technical focus will be on the development and evaluation of novel algorithms, computational models, and associated software techniques for robust, lightweight, and real-time temporal processing. The PhD research will draw on a combination of publicly available datasets and proprietary data generated within Ulster University’s research laboratories and Thales UK Ltd.

This project is available in the Computer Science Research Institute and is tenable in the Faculty of Computing, Engineering and the Built Environment, at the Magee campus. The PhD researcher will be based at the Intelligent Systems Research Centre and become part of a vibrant, interdisciplinary environment, drawing on the strengths of Ulster’s Cognitive and Computational Neuroscience, Neurotechnology, AI/ML, and Computational Biology communities. The PhD researcher will gain training in:

* AI and ML
* Computational modelling of behaviour and brain function
* High-performance computing
* Applied mathematics and statistics
* Neuroscience and cognitive science

Ulster University provides a supportive and research-intensive environment, ranked 2nd in the UK for PhD researcher satisfaction, and home to one of the largest and most impactful Computer Science and Informatics research units in the country. Thales is a major international company operating in the Digital Identity and Security, Defence and Security, Aeronautics, Space and Ground Transportation sectors.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• Applicants should hold, or expect to hold a First Class Honours Degree in a relevant subject area
• International applicants should hold, or expect to hold a relevant Masters Degree at a level equivalent to a distinction at Ulster
• Work experience relevant to the proposed project
• Track record of peer reviewed publications
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• DfE CDP Award in collaboration with Thales IAS
• Vice Chancellor's Research Scholarship (VCRS)

PhD Scholarships are available for this project and will cover:

• Tuition fees.
• A maintenance allowance of approximately £28,000 (exact rate is to be confirmed) per annum for three years, subject to satisfactory academic performance.
• A Research Training Support Grant (RTSG) of approximately £900 per annum.

To be eligible for these scholarships applicants must: be a UK or Irish national; or have pre-settled or settled status; or have indefinite leave to remain or enter.

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme i.e. September 2027.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year, or part-time equivalent, funded from any source, including self-financing students, are NOT eligible to apply for an award.

Students in full-time employment are not eligible for an award.

Due consideration should be given to financing your studies.

Part-time PhD scholarships may be available at a 0.5 pro rata rate of the full-time scholarship, which would require a six-year registration period.

The University will award a successful candidate one of the following scholarships for the project, depending on the funding available at the time an admissions offer is made:

1. Department for the Economy (DfE) PhD Scholarships
2. Vice Chancellor’s Research Scholarships (VCRS)

Please note that the Terms and Conditions for scholarships are subject to change for 2027/28.