RAEng Google DeepMind Research Ready Summer Internships 2026
Google DeepMind Research Ready is a pioneering new scheme supporting UK universities to deliver AI research placements for undergraduate students from socioeconomically disadvantaged backgrounds and underrepresented groups within engineering.
The Research Ready Internship was invaluable to my professional development. It gave me the opportunity to work in an academic setting while also completing an end-to-end data science project using real Airbus data, bridging the gap between theory and real-world application.
Abhishek Dey
The scheme is a partnership between the Royal Academy of Engineering, Google DeepMind and the Hg Foundation.
In summer 2025, it funded over 100 paid AI research placements hosted by 12 UK universities, providing students with research experience, tools and opportunities to excel in AI research.
About the programme
It aims to widen participation in AI research by addressing barriers encountered by undergraduates from socioeconomically disadvantaged and underrepresented backgrounds in progressing to advanced degrees and careers in AI. In doing so, it will build a stronger, more diverse AI research community that can bring unique perspectives and solutions to the field.
The programme will support eligible undergraduates to improve their knowledge of the different areas of AI, build their research expertise, understand the routes into different AI careers, and build confidence in taking the next steps in their education or career journey in AI.
Residency and academic criteria
You must meet all the following:
- Be a UK resident and eligible to pay UK home fees.
- Have, or expect to have, the right to live and work full time in the UK for the duration of the programme and can provide proof.
- Are within the penultimate or final year of their undergraduate degree, or have already completed an undergraduate degree, in computer science or an AI facilitatory-related technical field.
- Are not currently studying for or have completed a master’s degree or PhD.
Socioeconomic criteria
In additional to the above, you must provide evidence that you meet at least one of the following:
- Have been eligible for free school meals.
- Live in an area in the lowest two deciles according to a postcode measure such as IMD or POLAR.
- Have at some stage been in local authority care.
- Have been in receipt of full state support for maintenance for their course of undergraduate study.
- Have had caring responsibilities for 3 months or more, which either have occupied more than 10 hours per week, or which have impacted on the applicant’s education, health or wellbeing.
- Receive/received the maximum Maintenance Loan for undergraduate study.
Available projects
During your application, you will be asked to select three of the following projects*:
Projects available soon.
*There is one internship per project. We cannot guarantee that you will be offered a place on one of your chosen projects.
Applications for summer 2026 are now open and will close at 23:59 (UK time) on Sunday 1 March.
To apply, please complete all the mandatory sections in the application form.
If you have any questions, please email ai-fun@manchester.ac.uk.
Hear from students who took part last year
The meetings with my supervisor and being in the research group gave me a glimpse of postgraduate life.
Kaventthan Sivachelvan
The support and encouragement I received from my second supervisor were invaluable. Some of the guest lectures were really interesting, particularly the SpiNNaker session. I gained first-hand experience of academic research and worked on an interesting and prestigious project.
Bradley Booth
My supervisor tailored the internship goals to my existing skill set, which allowed me to go well beyond the original scope and develop a more rigorous academic project. Through this, I gained substantial experience and deepened my understanding of applied statistics and data science.
Most importantly, the internship helped legitimise my profile as a candidate for statistics and data science roles. Coming from a Physics background with primarily physics-based projects, I previously received far fewer interviews. The combination of the project itself and the credibility added by funding from Google DeepMind and the Royal Academy of Engineering made this experience a key talking point. It was also a major reason I progressed to the final stage and secured the role I have now.
Abhishek Dey