Research Associate in AI & Wireless Communications

Grade & Salary: Grade 7, £37,694 - £47,389 per annum

FTE & Working Pattern: Full‑time (35hrs per week), Fixed‑term (6 months)

Reward & Benefits: 33 days annual leave, plus 9 bank closed days for all full‑time staff.

About our Team: The School of Engineering & Physical Sciences has an international research reputation and close connection with the professional and industrial world of science, engineering and technology. Our research ranges from fundamental sciences through to engineering applications, all of which are supported by strong external funding. We have around 150 full‑time academic staff who drive this research activity and are based in 5 research institutes: the Institute of Chemical Sciences, the Institute of Photonics & Quantum Sciences, the Institute of Mechanical, Process & Energy Engineering, the Institute of Sensors, Signals & Systems and the Institute of Biological Chemistry, BioPhysics & BioEngineering. REF2014 named Heriot‑Watt in the top 25% of UK universities, with 82% of our research ranked as world‑leading or internationally excellent. Heriot‑Watt ranked 9th university in the UK and 1st in Scotland for research impact.

Purpose of Role: We are seeking to recruit a highly motivated PDRA willing to work as part of a team in this project to support the development of AT‑native 6G wireless communications and robotic networking for healthcare. Applicants must have a PhD degree (or have submitted a PhD thesis) in Electrical, Electronic, Computer Engineering, Computer Science or a related discipline, have excellent knowledge and strong background in Signal Processing for wireless communications/networks (in particular physical/cross‑layer technologies), MIMO signal processing, interference management, machine learning, beamforming, precoding, channel estimation, IoT, user interface technologies, mathematics and optimisation evidenced by high‑quality research publications. Applicants must also have excellent written, oral presentation, and interpersonal skills, and software programming skills (Matlab and/or C/C++/JAVA/Python) appropriate for wireless communications simulation and testbed (USRP) work. It is desirable that the applicants have some industrial experience working in telecommunications, machine learning, networks, programming or testbed. The project provides an excellent opportunity for career development and to make an important contribution to a very challenging field in wireless communications and will offer an opportunity to work with world‑leading researchers. Possible placement opportunities with Nokia Bell Labs will be available through this post.

The successful candidate will join the digital signal processing for intelligent systems and communications (SPCOM), Institute of Sensors, Signals and Systems (ISSS), supervised by Prof Mathini Sellathurai.

Key Duties & Responsibilities:

• Develop research objectives and proposals for own or joint research with the assistance of a mentor, if required.
• Conduct individual and collaborative research projects, making use of relevant research techniques and methods.
• Disseminate results of research in peer‑reviewed journals and conferences, and/or other appropriate media.
• Continue to update personal knowledge and to develop skills within own specialist research area.
• Maintain written records of research results and progress, generate intellectual property and data analysis, and contribute to the production of research reports and publications.
• Write research reports and publications.
• Analyse and interpret the results of own research and generate original ideas based on outcomes.
• Prepare proposals and applications to external bodies, for funding purposes.
• Use initiative and creativity to identify areas for research, develop new research methods and extend the research portfolio.
• Build internal contacts and participate in internal networks for the exchange of information and to form relationships for future collaboration.
• Work with academic colleagues on areas of shared research interest and contribute to collaborative decision making.
• Join external networks to share information and identify potential sources of funds.
• Contribute, under supervision, to the planning of research projects, including the development of new grant/contract proposals.
• Make internal and external contacts to develop knowledge and understanding and form relationships for future collaboration.

We are looking for a creative and highly motivated researcher willing to work as part of a team. The ideal candidate will have a strong theoretical understanding and an experimental background in one or more of the following fields: Signal Processing, Machine Learning, Wireless Communications, IoT, Wireless USRP Testbeds. Good communication skills and an appropriate publication record are essential. A working knowledge of Python and C programming are desirable.

General tasks will involve scientific research; analysis and interpretation of data; daily oversight of the activities of postgraduate and undergraduate project students in the laboratory; communication with other investigators involved in this collaborative project; preparation of scientific papers; presentation of research at conferences. The successful candidate will be expected to conduct and lead their own experiments whilst also supervising the activities of junior group members and PhD students. Responsibilities will also include assistance in the day‑to‑day maintenance of the experimental facilities, liaising with companies and external collaborators. The successful candidate is also expected to be involved in our outreach activities, with roles that can be tuned to the specific preferences of the candidate but will involve, for example, interviews, talks for the general public and preparation of experimental demonstrators.

Person Specification:

These are the criteria on which the short‑listing and recruitment selection will be made.

Essential:

• Possess and maintain sufficient breadth or depth of specialist discipline knowledge and research methods and techniques to work in own area.
• Applicants should hold a PhD (or submitted PhD thesis before the start date) in a relevant area of Electrical Engineering or Computing or related subject.
• A record of high‑quality publications, and evidence of contribution to the writing of these publications proportionate to opportunity.
• Must have proven academic ability and a demonstrable high level of technical competence in signal processing and wireless communications.

Desirable:

• Evidence of ability to present work effectively in person, e.g. at conferences and seminars.
• Previous experience with one or more of the following: Wireless Communications, IoT, Machine Learning and Wireless USRP Testbeds.
• Experience in leading the writing of scientific papers.
• Experience of programming for data acquisition (e.g. LabVIEW, Matlab, Python) and analysis.
• Experience of experimental design and integration.
• Evidence of ability, subject to opportunity, to guide other researchers, e.g. PhD students and undergraduate project students.
• Experience of research‑student supervision.
• Capability to be self‑directed and think innovatively.
• Energy and enthusiasm for the project.

How to Apply: Please submit via the Heriot‑Watt online recruitment system: (1) Cover letter describing your interest and suitability for the post; (2) Full CV. Applications can be submitted until 23:55 on Tuesday 9 June 2026.

Equality, Diversity and Inclusion: Heriot‑Watt University is committed to securing equality of opportunity in employment and to the creation of an environment in which individuals are selected, trained, promoted, appraised and otherwise treated on the sole basis of their relevant merits and abilities. Equality and diversity are all about maximising potential and creating a culture of inclusion for all. Heriot‑Watt University values diversity across our University community and welcomes applications from all sectors of society, particularly from underrepresented groups.

We welcome and will consider flexible working patterns, e.g. part‑time working and job share options.