Research Fellow in AI for Software Engineering

RFCSR; Belfast City District; On-site; GBP 36,000 - 48,000; Full time

Job summary

Queen’s University Belfast invites applications for a Postdoctoral Research Fellow to advance AI for Software Engineering in a Horizon Europe project on Highly Automated/Autonomous Driving Systems. The role involves developing software and contributing to collaborative research with international partners.

You will publish results, work with researchers and industry partners, and gain hands-on experience with AI computing and Autonomous Vehicle facilities.

Qualifications

• PhD with relevant research in Artificial Intelligence, Software Engineering, or Autonomous Vehicles.
• Strong research background and interest in Artificial Intelligence, Software Engineering, or Autonomous Vehicles.
• Demonstrated evidence of publication in top international journals and conferences.
• Proven experience in software development for real-world applications or simulation environments.
• Excellent ability to communicate complex information effectively in English, both orally and in writing.

Responsibilities

• Developing software for Queen’s University Belfast’s Autonomous Vehicle Research Platform.
• Publishing research results in top international journals and conferences relevant to the field.
• Collaborating with established academics, early‑career researchers, research engineers, and international project partners.
• Periodically traveling to participate in project meetings and present research at international conferences.

Skills

Research skills

Software development

Communication

Collaboration

Education

PhD in AI/SE/AV

Job description

Research Fellow in AI for Software Engineering

Queen’s University Belfast is seeking a highly motivated Postdoctoral Research Fellow to primarily contribute to a Horizon Europe project focusing on the use of Artificial Intelligence for Software Engineering for Highly Automated/Autonomous Driving Systems (Autonomous Vehicles). The successful candidate will also contribute to other relevant research activities within the Connected and Cooperative Autonomous Systems research group.

As a key member of a well-established and highly experienced team of researchers and academics, the appointee will work collaboratively with international academic and industry partners, including major European companies in the Automotive, ICT, and Software Engineering sectors. The post offers a unique opportunity to develop professional skills, build strong collaborative networks, and gain hands‑on experience using QUB’s advanced AI computing and Autonomous Vehicle Research Facilities with real-world systems.

Key duties and responsibilities include:

• Developing software for Queen’s University Belfast’s Autonomous Vehicle Research Platform.
• Publishing research results in top international journals and conferences relevant to the field.
• Collaborating with established academics, early‑career researchers, research engineers, and international project partners.
• Periodically traveling to participate in project meetings and present research at international conferences.

Additional Information:

Job Reference: 26/113554

Hours: Full Time

Contract Type: Fixed-Term / Contract (Initially 12 months with the possibility of extension)

A PhD with relevant research in Artificial Intelligence, Software Engineering, or Autonomous Vehicles (applicants who have submitted their thesis, passed their viva voce examinations, and are awaiting the formal award of their PhD are also welcomed).

Strong research background and interest in Artificial Intelligence, Software Engineering, or Autonomous Vehicles.

Demonstrated evidence of publication in top international journals and conferences.

Proven experience in software development for real-world applications or simulation environments.

Practical problem‑solving skills, independence of thought, and initiative.

Excellent ability to communicate complex information effectively in English, both orally and in writing.

Strong interpersonal skills to build relationships and develop internal and external networks.

Ability and desire to work effectively as part of a team with minimal supervision.