Research Fellow in Edge AI security
Research Fellow in Edge AI security

Research Fellow in Edge AI security

Belfast Full-Time 28800 - 48000 £ / year (est.) No home office possible
Q

At a Glance

  • Tasks: Join us in tackling security challenges in edge AI systems and design secure AI accelerators.
  • Company: Queen's University Belfast is a leading institution committed to equality and diversity.
  • Benefits: Enjoy a supportive work environment with opportunities for professional growth and collaboration.
  • Why this job: Make an impact in AI security while working on cutting-edge technology in a vibrant research community.
  • Qualifications: PhD or nearing completion in relevant fields, with expertise in AI security and embedded systems.
  • Other info: This is a 12-month fixed-term contract with potential for renewal based on funding.

The predicted salary is between 28800 - 48000 £ per year.

Research Fellow in Edge AI security, Belfast

Client:

Queen\’s University Belfast

Location:

Belfast, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Reference:

1392e3ccd0cd

Job Views:

10

Posted:

12.08.2025

Expiry Date:

26.09.2025

Job 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.
  • The candidate will 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.
  • 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 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 in particular circumstances may be renewed or made permanent subject to availability of funding.

What we offer:

Queen\’s University is committed to promoting equality of opportunity to all. We subscribe to Equality Charter Marks such as the Diversity Charter Mark NI and Athena Swan and have established staff networks such as iRise (Black, Asian, Minority Ethnic and International Staff Network) and PRISM (LGBTQ+) which help us progress equality.

If you are an international applicant and don\’t already hold a visa that permits you to take up the role you are applying for, please use the information provided on our website to self-assess whether the University is likely to be able to support a visa application.

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Research Fellow in Edge AI security employer: Queen's University Belfast

Queen's University Belfast is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration in the field of Edge AI security. With a strong commitment to equality and diversity, the university provides numerous opportunities for professional growth and development, alongside access to cutting-edge research facilities in a dynamic academic environment. Located in Belfast, employees benefit from a rich cultural scene and a supportive community, making it an ideal place for those seeking meaningful and rewarding careers in academia.
Q

Contact Detail:

Queen's University Belfast Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Fellow in Edge AI security

✨Tip Number 1

Familiarise yourself with the latest research and developments in Edge AI security. This will not only help you understand the challenges but also allow you to discuss relevant topics during interviews, showcasing your passion and knowledge in the field.

✨Tip Number 2

Network with professionals in the AI and embedded systems community. Attend conferences, webinars, or local meetups to connect with researchers and industry experts. This can lead to valuable insights and potentially even referrals for the position.

✨Tip Number 3

Engage in hands-on projects related to Edge AI and security. Whether it's through personal projects, collaborations, or contributions to open-source initiatives, practical experience will strengthen your profile and demonstrate your commitment to the field.

✨Tip Number 4

Prepare to discuss your previous research and its impact on the field. Be ready to articulate how your work aligns with the goals of the Research Fellow position, particularly in relation to hardware-aware AI security and performance-security trade-offs.

We think you need these skills to ace Research Fellow in Edge AI security

PhD in Computer Science, Engineering, Mathematics, or related physical sciences
Research expertise in hardware-aware AI security
Experience with approximate computing
Knowledge of secure embedded AI systems
Strong track record of high-quality research in machine learning/AI
Publications in leading conferences and journals
Hands-on experience with Edge AI and embedded systems security
Proficiency in Python programming
Familiarity with hardware design (Verilog/VHDL)
Experience with FPGA-based acceleration
Knowledge of deep learning frameworks (PyTorch, Keras, TensorFlow)
Proficiency in using Jupyter Notebook
Strong foundation in core machine learning theory (statistics, optimisation, linear algebra)
Ability to independently develop and execute research plans
Track record of successful collaboration with industry partners

Some tips for your application 🫡

Understand the Role: Thoroughly read the job description for the Research Fellow position. Make sure you understand the specific requirements, such as expertise in hardware-aware AI security and experience with Edge AI systems.

Highlight Relevant Experience: In your application, clearly demonstrate how your background aligns with the essential and desirable criteria listed. Include specific examples of your research, publications, and hands-on experience with AI security and embedded systems.

Tailor Your CV: Customise your CV to reflect the skills and experiences that are most relevant to the position. Emphasise your proficiency in Python, familiarity with hardware design, and any experience with deep learning frameworks.

Craft a Strong Cover Letter: Write a compelling cover letter that outlines your motivation for applying and how your research interests align with the goals of the position. Be sure to mention any collaborative projects with industry partners that showcase your ability to work independently and as part of a team.

How to prepare for a job interview at Queen's University Belfast

✨Showcase Your Research Experience

Be prepared to discuss your previous research projects in detail, especially those related to AI security and embedded systems. Highlight any publications or presentations you've made, as this demonstrates your expertise and commitment to the field.

✨Demonstrate Technical Proficiency

Make sure you can talk confidently about your experience with programming languages like Python and any hardware design tools you’ve used, such as Verilog or VHDL. Familiarity with deep learning frameworks like PyTorch or TensorFlow will also be beneficial.

✨Understand the Role's Challenges

Research the specific security challenges faced by edge AI systems, such as side-channel attacks and fault injections. Being able to articulate these issues and propose potential solutions will show your depth of understanding and readiness for the role.

✨Prepare for Collaboration Questions

Since collaboration with industry partners is key, think of examples from your past where you successfully worked in a team. Be ready to discuss how you contributed to group projects and what you learned from those experiences.

Research Fellow in Edge AI security
Queen's University Belfast

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