Research Fellow in Applied AI and Cybersecurity

The University of Bedfordshires Luton AI initiative is seeking a talented Research Fellow in Applied AI and Cybersecurity to develop new approaches to identifying unmanaged wireless and Internet of Things (IoT) security threats.

The post forms part of SAZT-Wi-Fi (Spatial-Aware Zero-Trust Platform for Shadow Wi-Fi IoT Threat Detection) an Innovate UK-funded project developing a standalone plug-and-play cybersecurity proof of concept for critical infrastructure.

Luton AI is the University of Bedfordshires growing applied AI research and innovation initiative connecting researchers engineers and industry partners to solve real-world problems. Since 2024 we have engaged more than 600 organisations and undertaken over 60 bespoke AI projects spanning aviation public services cybersecurity and critical infrastructure. Our expanding AI computing and cybersecurity facilities support the development of new technology from early research to working demonstrators. You will join a collaborative interdisciplinary team focused on turning ambitious technical ideas into useful deployable solutions.

Working with Luton AI academics and industry partners you will lead day-to-day technical development and integration of a working proof of concept combining Wi-Fi radio-frequency (RF) telemetry machine learning cybersecurity software and locally deployed AI for human-readable threat explanations.

You will translate research into a functional demonstrator with an emphasis on robust software reproducible experimentation and evaluation in realistic environments.

• Capturing and processing Wi-Fi RF metadata and network telemetry through passive monitoring and commercially available sensing technologies.
• Building data ingestion processing and analysis pipelines for wireless telemetry.
• Designing training and evaluating machine learning methods to detect anomalous unmanaged or potentially malicious IoT activity.
• Combining spatial behavioural RF and network features with local large language models to explain detected threats.
• Developing Python-based services APIs an accessible dashboard and interfaces with SIEM/SOC security tooling.
• Testing benchmarking and refining the integrated proof of concept documenting performance and limitations.
• Collaborating with academic and industry partners and contributing to reports demonstrations technical documentation and research or IP outputs.

We are looking for a technically capable self-directed researcher who enjoys developing working systems. You will have:

• A good honours degree or equivalent professional experience in Computer Science Cybersecurity AI Data Science Electronic Engineering or a related discipline.
• Strong Python software development skills and knowledge of machine learning for anomaly detection or classification.
• An understanding of Wi-Fi/network telemetry and cybersecurity with practical experience analysing wireless or network data.
• Experience developing end-to-end data or software prototypes and evaluating models on real-world data.
• The ability to manage technical delivery document findings and collaborate with academic and external partners.

Experience with local LLMs edge deployment RF sensing Linux containerisation APIs or SIEM/SOC integration would be advantageous.

For an informal discussion please contact Dr Edward Braund Head of School and Director of Luton AI on or

For a full job description and person specification please click here

The post will be based at Luton (with travel to other campuses as required)

Interview date is w/c 23rd Nov 2026.

The University is committed to equality of opportunity and values the diversity of all its workforce and student population.

At the University of Bedfordshire inclusivity is a key University value and we are committed to creating an environment in which we celebrate and value the diversity of our staff and student community and provide fair opportunity and outcomes for all.

We recognise that diversity fosters creativity and innovation and we want our community to represent and benefit from opportunities that the diversity of talent and thought creates.

We therefore particularly encourage applications from candidates who are likely to be underrepresented in the University of Bedfordshires workforce. These include people from Black Asian and Ethnic Minority backgrounds (particularly in roles in grades 7 and above) disabled people; LGBTQ people; and women in some senior grades.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

We offer a range of employee benefits including a generous pension and annual leave entitlement free fitness classes and gym membership flexible working arrangements personal and professional development and family-friendly policies. For further details please click here

To Apply

Please visit our website any enquires contact People & Culture email P&

Please note a Curriculum Vitae will only be accepted if accompanied by a fully completed University application form.