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- Tasks: Join a cutting-edge research team to develop innovative AI systems and network protocols.
- Company: Brunel University London, a leader in research and innovation.
- Benefits: Generous salary, waived tuition fees, hybrid working, and excellent training opportunities.
- Other info: Inclusive environment with strong support for career development.
- Why this job: Make a real impact in AI research while earning a fully funded PhD.
- Qualifications: Background in computer science, machine learning, or related fields required.
The predicted salary is between 40757 - 40757 £ per year.
This PhD scholarship is part of the EU Horizon Europe Marie Skłodowska‑Curie Actions Doctoral Network (MSCA DN) project ANT – Embedded AI Systems and Applications.
Location: Brunel University of London, Uxbridge Campus
Salary: £40,757 per annum inclusive of London Allowance. The university will waive international PhD tuition fees for the duration of the program.
Contract Type: Fixed‑term for 29 months, followed by a 7‑month stipend at the UKRI rate (approximately £1,983.75 per month).
Research Scope: Project ANT offers 18 fully funded PhD positions aimed at advancing research in embedded and networked AI systems.
Responsibilities:
- Develop networked scalable learning techniques that accommodate dynamic topology, computing loads, data volume, resource availability, and quality of service (QoS) requirements.
- Design network protocols to facilitate networked scalable learning.
- Develop optimisation schemes for dynamic resource allocation and computing load distribution.
Candidate Profile: Candidates should have a background in computer science, machine learning, electrical engineering, telecommunication engineering, applied mathematics, or related areas.
Desirable Skills / Interests: Machine learning, large language models, signal processing, wireless communications, applied optimisation.
Secondments:
- ST (3 months, M16‑M18, may be rescheduled): Networked scalable and continual learning in dynamic evolving environment.
- IMEC (4 months, M27‑M30, may be rescheduled): Efficient data transfer protocols for networked scalable learning.
Benefits:
- Annual leave package plus discretionary university closure days.
- Excellent training and development opportunities.
- Occupational pension scheme.
- Family allowance may be payable on eligibility and supporting evidence.
- Health‑related support services.
- Hybrid working approach.
- Research training and network fees available up to £50,139.84 for 3 years.
Contact: For an informal discussion, please email Professor Kezhi Wang at . The University is fully committed to creating and sustaining an inclusive workforce. We welcome applicants from all backgrounds and communities, especially those currently under‑represented in our workforce.
Research Assistant (MSCA) with PhD Full Scholarship - 16044 in London 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 (MSCA) with PhD Full Scholarship - 16044 in London
✨Tip Number 1
Network like a pro! Reach out to current or former PhD students at Brunel University, especially those in the ANT project. They can give you insider info and maybe even put in a good word for you.
✨Tip Number 2
Prepare for your interview by diving deep into the research scope. Familiarise yourself with networked scalable learning techniques and optimisation schemes. Show us you’re not just a fit on paper but also passionate about the project!
✨Tip Number 3
Don’t underestimate the power of a follow-up! After your interview, shoot a quick thank-you email to express your appreciation. It keeps you fresh in their minds and shows your enthusiasm for the role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Research Assistant (MSCA) with PhD Full Scholarship - 16044 in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Assistant role. Highlight relevant experience in computer science, machine learning, or any related fields. We want to see how your skills align with the project ANT and its focus on embedded AI systems.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this PhD opportunity and how your background fits the responsibilities outlined in the job description. Let us know what excites you about the research scope!
Showcase Your Skills: Don’t forget to showcase any specific skills or projects that relate to networked scalable learning or optimisation schemes. We’re looking for candidates who can demonstrate their expertise in these areas, so make it clear how you can contribute to our team.
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 to complete your application there!
How to prepare for a job interview at Brunel University of London
✨Know Your Research
Dive deep into the specifics of the ANT project and its focus on embedded AI systems. Familiarise yourself with recent advancements in networked scalable learning techniques, as well as the challenges faced in dynamic environments. This will show your genuine interest and understanding of the role.
✨Showcase Relevant Skills
Prepare to discuss your background in computer science, machine learning, or related fields. Highlight any projects or experiences that align with the responsibilities listed, such as designing network protocols or developing optimisation schemes. Be ready to provide examples that demonstrate your expertise.
✨Ask Insightful Questions
Prepare thoughtful questions about the research scope and secondments mentioned in the job description. Inquire about the team dynamics, collaboration opportunities, and how the university supports research training. This not only shows your enthusiasm but also helps you gauge if the position is the right fit for you.
✨Emphasise Inclusivity
Since the university values diversity, be prepared to discuss how your unique background or perspective can contribute to an inclusive research environment. Share any experiences that highlight your commitment to fostering a diverse workplace, which aligns with the university's mission.