Postdoctoral Research Fellow in AI security

European Commission; United Kingdom; On-site; GBP 30,000 - 45,000; Full time

Job summary

A leading university in the UK seeks a Research Fellow to focus on AI security for edge devices. The ideal candidate will hold a PhD and have expertise in machine learning and AI security. Responsibilities include designing secure AI accelerators and analyzing threats in hardware-constrained environments. An attractive benefits package is offered, including generous holiday entitlement and flexible working options.

Benefits

Competitive salary

Attractive benefits package including up to 8.4 weeks holiday

Flexible working options

Qualifications

• Expertise in AI security for hardware-constrained devices is essential.
• Research background in machine learning/AI with publications is a must.
• Hands-on experience with Edge AI and embedded systems security is desirable.

Responsibilities

• Design secure AI accelerators for edge devices.
• Analyze attack surfaces and develop security frameworks.
• Collaborate with industry partners on research projects.

Skills

Machine learning/AI research

AI security

Deep learning frameworks (PyTorch, Keras, TensorFlow)

Approximate computing

Python programming

Education

PhD in computer science, engineering, mathematics, or related

Tools

Jupyter Notebook

Verilog/VHDL

Job description

Organisation/Company Queen's University Belfast Research Field Computer science » Other Researcher Profile Leading Researcher (R4) Established Researcher (R3) Country United Kingdom Application Deadline 25 Aug 2025 - 00:00 (UTC) Type of Contract To be defined Job Status Negotiable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The emergence of edge AI systems—AI deployed on resource-constrained, often battery-powered, devices at the edge of the network—presents critical security challenges. These systems are increasingly vulnerable to hardware-level threats, including side-channel attacks, fault injections, etc., particularly when optimized for performance.

This Research Fellow position focuses on AI security in the context of hardware-constrained edge devices, investigating how hardware acceleration can be leveraged by adversaries to compromise AI systems' robustness. The role involves designing secure AI accelerators, analyzing attack surfaces introduced by approximation, and developing a performance-security trade-off framework to guide secure AIoT deployment.

About the person:

The successful candidate will have, or be close to obtaining, a PhD in computer science, engineering, mathematics, or a related physical sciences discipline, with research expertise in areas such as hardware-aware AI security, approximate computing, or secure embedded AI systems.

They will demonstrate a strong track record of high-quality research in machine learning/AI and/or embedded systems, evidenced by publications in leading conferences and journals.

Experience with deep learning frameworks like PyTorch, Keras, or TensorFlow, and tools such as Jupyter Notebook, is expected.

A strong foundation in core machine learning theory—including statistics, optimization, and linear algebra—is desirable.

The candidate will ideally have hands-on experience with Edge AI and embedded systems security, as well as a solid grounding in AI security and Trustworthy AI.
They will be proficient in Python and ideally familiar with hardware design (Verilog/VHDL), FPGA-based acceleration, etc.

The ideal candidate will have a proven ability to independently develop and execute research plans and a track record of successful collaboration with industry partners.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information.

This post is available for 12 months. Fixed term contract posts are available for the stated period in the first instance but may be renewed or made permanent subject to availability of funding.

What we offer:

Beyond a competitive salary, the University offers an attractive benefits package including a holiday entitlement of up to 8.4 weeks a year, pension schemes and development opportunities. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at Human Resources

Queen's University is committed to promoting equality of opportunity to all.
For further information on our commitment to Equality, Diversity and Inclusion, please visit Diversity .

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