Skip to main content
Digital Environment Research Institute (DERI)

Queen Mary students successfully awarded placements at The Alan Turing Institute

Four postgraduate research students from Queen Mary University of London have successfully been awarded an Enrichment placement at The Alan Turing Institute. They will be able to gain valuable research experience through the placements.

Published:

The students who will be joining the scheme are Binur Orazumbekova, Eisa Anwar, Shubhr Singh and Teresa Pelinski.

Now entering its eighth year, the Turing Enrichment scheme is designed for PhD students to broaden their current research by accessing the facilities and opportunities available at the renowned Alan Turing Institute. Throughout the six or nine-month placement, enrichment students can collaborate and network with their peers, as well as leading experts, develop research independence and join a bustling community of students and researchers based at Turing’s office in London.

The 2023/24 Enrichment scheme has also introduced new initiatives this year including creating stronger research connections by facilitating links between students and Turing’s research community. Enrichment students are also eligible for funding to support training activities such as participation in conferences and courses.

Previous recipients from Queen Mary have spoken of how the overall experience as well as the training events and courses offered benefited their research, and that the environment allowed students to thrive on collaboration and look at their research with new perspectives and from different disciplines. 

Berker Banar, a computer scientist, musician and PhD researcher at the Centre for Doctoral Training in Artificial Intelligence and Music and Centre for Digital Music at Queen Mary said: “The diverse background of the researchers was one of the best parts of being at the institute and I’ve learned that there are so many different ways to approach the same problem, where each of these ways can bring unique advantages to the table. After my time there, I feel more confident about collaborating with researchers from various backgrounds and how to make the best of different views from various backgrounds working on the same problem analogically.”

Queen Mary’s Dr Emmanouil Benetos, a Reader in EECS, a Turing Fellow and member of the Enrichment Scheme applicant review panel, said: “The biggest benefit that students gain from the institute is access to a community of experts in data science and artificial intelligence across the UK. Students are able to carry out their research from the Turing's headquarters in London which will offer plenty of engagement and networking opportunities, as well as provide them with access to the wider Turing community. They will also be gaining access to a wide range of training opportunities for boosting their research skills.

“The Enrichment placements also gives students the potential to significantly boost their research profile and visibility and offer an ideal route for establishing new collaborations and networks, allowing the students to become independent researchers and hopefully future leaders in topics related to data science and AI.”

Professor Greg Slabaugh, Turing Liaison (Academic) at Queen Mary and Director of the Digital Environment Research Institute, said: “The Enrichment scheme offers PhD researchers an opportunity to broaden their horizons whilst on placement working with the Turing community. Award holders receive enhanced collaboration, attend events and networking facilitated through a placement award and physical access to The Alan Turing Institute. PhD students can develop their research independence, engaging with new ideas and researchers in the Turing, whilst enhancing their network in preparation for their careers post-PhD.”

Queen Mary first joined the Institute as a university partner in 2018, and was one of the original 36 universities who joined the pilot Turing University Network in April 2023 ahead of the official launch in October 2023, which saw a total of 65 partners join the Network under the new model. As a member, Queen Mary will be able to further its data science and AI aims through easier engagement and collaboration with both the Institute and its broader networks, such as industry partners.

Vera Matser, Head of Skills at The Alan Turing Institute, said: “The Enrichment scheme is central to our work to build skills for the future. We’d like to extend a warm welcome to all of the new students joining the Turing community and we look forward to working closely with them.” 

Joining this year’s scheme is Eisa Anwar, a Robotics PhD student with the Centre for Advanced Robotics at Queen Mary. His PhD involves building wearable technology to support human balance. Commenting on her opportunity Eisa said: “I plan to use the Institute’s facilities and expertise to develop my skills in Artificial Intelligence and Machine Learning. It will also be a great opportunity for me to learn more about how these technologies can be developed effectively and responsibly, taking into account the current challenges we face and how to overcome them.

"I’m most looking forward to using Artificial Intelligence to develop a new control system for my PhD project in wearable robotics. The use of Machine Learning could help my robot better adapt to different people and I plan to run experiments to test how well it works.“

Also joining this year’s scheme is Binur Orazumbekova, PhD student in the Health Data in Practice program at the Wolfson Institute of Population Health at Queen Mary. “I hope that during the six months I will be able to learn new methodologies, network with other PhD students from across the UK and bring something new to my research on Ethnic Inequalities in Diabetes. The scheme will help me to have new interdisciplinary collaborations that can help to generate new ideas for future research goals.”

Applications for the 2024 Enrichment scheme will open on 22nd November 2023. Please visit the Scheme's website page for more information on how to apply.

 

 

Back to top