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- Tasks: Join a cutting-edge project on AI and Large Language Models at Brunel University.
- Company: Brunel University London, known for its innovative research and collaborative environment.
- Benefits: Enjoy generous leave, training opportunities, and a competitive pension scheme.
- Why this job: Make a real impact in AI research while developing your skills in a dynamic team.
- Qualifications: PhD in relevant fields and experience with AI and Generative Adversarial Networks required.
- Other info: Hybrid working model with excellent career growth potential.
The predicted salary is between 36644 - 38638 £ per year.
We are seeking to appoint a Research Assistant who will work on the ELOQUENCE European project – a study focusing on Large Language Models in Artificial Intelligence – at Brunel University London. The successful candidate will develop AI technologies relevant to LLMs as part of a multidisciplinary consortium.
Responsibilities:
- Collaborate with the project team to design, train and evaluate AI and Large Language Model architectures.
- Conduct regular project meetings, give presentations and coordinate with internal and external consortium members via oral and written communication.
- Prepare and submit project reports, and co‑author research papers for publication.
- Travel as required for meetings and conferences.
Qualifications:
- Currently pursuing or holding a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic Engineering or a related discipline.
- Substantial research experience in Artificial Intelligence, particularly in designing, training and testing Generative Adversarial Networks.
- Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, Keras or equivalent toolboxes.
- Hands‑on experience with Large Language Models and a demonstrable record of related projects.
Employment Details:
- Contract Type: Fixed term until 31 December 2026
- Hours: Full‑time
- Salary: £36,644 to £38,638 per annum (inclusive of London weighting) with potential progression to £39,682 per annum (inclusive of London weighting)
- Location: Brunel University London, Uxbridge Campus
Benefits:
- Generous annual leave package, discretionary university closure days, excellent training and development opportunities, a competitive occupational pension scheme and health‑related support.
- The role embraces a hybrid working approach.
Application:
- Closing date for applications: 11 February 2026
- Ref No: 5028
- To apply and for further details, please visit Brunel Careers.
- For technical issues, contact hrsystems@brunel.ac.uk.
- Informal queries may be directed to Professor Tatiana Kalganova (tatiana.kalganova@brunel.ac.uk) or Dr. Nikolaos Boulgouris (nikolaos.boulgouris@brunel.ac.uk).
Equality and Diversity:
Brunel University wishes to promote an inclusive and diverse workforce and create a culture that values the contribution of all backgrounds and communities. All employees will be recruited, selected and appointed in line with our equality and diversity policy.
Research Assistant - 15563 in Uxbridge employer: Brunel University of London
Contact Detail:
Brunel University of London Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Assistant - 15563 in Uxbridge
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and research community. Attend relevant events or webinars, and don’t be shy about introducing yourself to potential colleagues or mentors. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to Large Language Models and AI. This could be anything from GitHub repositories to presentations. When you get the chance to chat with recruiters or during interviews, let your work speak for itself.
✨Tip Number 3
Prepare for those interviews! Research the ELOQUENCE project and be ready to discuss how your experience aligns with their goals. Practice common interview questions and think about how you can demonstrate your knowledge of Python and machine learning frameworks.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in the role. Don’t forget to follow up after applying; a little nudge can go a long way!
We think you need these skills to ace Research Assistant - 15563 in Uxbridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Assistant role. Highlight your experience with AI, LLMs, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for the ELOQUENCE project. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and any machine learning frameworks you’ve used. If you’ve worked with Generative Adversarial Networks or LLMs, make sure to highlight those experiences. We’re keen to see your technical prowess!
Apply Through Our Website: We encourage you to apply through our website for a smooth application process. It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need there!
How to prepare for a job interview at Brunel University of London
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Large Language Models and Generative Adversarial Networks. Be ready to discuss your hands-on experience with these technologies, as well as any relevant projects you've worked on. This will show that you're not just familiar with the theory but can also apply it in practice.
✨Showcase Your Collaboration Skills
Since this role involves working with a multidisciplinary team, be prepared to talk about your previous collaborative experiences. Think of specific examples where you successfully communicated and coordinated with others, whether in project meetings or while co-authoring research papers.
✨Prepare for Technical Questions
Expect some technical questions during the interview, especially related to Python and machine learning frameworks like TensorFlow or Keras. Brush up on your coding skills and be ready to solve problems on the spot or explain your thought process clearly.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the ELOQUENCE project’s goals, the team dynamics, or future opportunities for development. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
