Introduction
After a competitive application process, the Turing-Roche partnership is delighted to introduce its first cohort of Community Scholars. The year-long scholar scheme running from September 2023 to September 2024 has awarded 10 PhD students a stipend of £3000. The scholars will embed themselves within the partnership community, attend a relevant conference and undertake their own community-based project.
The scheme will give the scholars experience of this unique academic-industry partnership and help them develop skills that will benefit and further their careers. The community projects run by the scholars will give the partnership community and wider interested researchers further opportunities to engage in topics relevant to the partnership and data science and health more broadly.
You can find out more about each scholar and their projects from their individual pages and below. You can connect with the scholars through the partnership Slack Workspace.
Community Scholar Projects
Jack Breen, University of Leeds
Jack’s project will focus on developing a chapter for the Turing Way handbook about reducing risks of bias and improving the completeness of reporting in research. This chapter will include an exploration of how research results can be misleading due to limitations of the study design, conduct, and analysis, and will act as a guide to researchers to improve the reliability and reproducibility of their research. The chapter will be developed collaboratively with input from an array of researchers in different disciplines.
Tom Butters, University College London
Thomas’s project is to run a short series of workshops in conjunction with the Turing-Roche team which would bring together clinicians and computer scientists in order to:
1. Consider the challenges of AI in healthcare, and share knowledge on creative methods to overcome them.
2. Dispel myths surrounding the use of AI in healthcare.
3. Consider how AI might be applied to serve unmet needs in the medical community.
Sarah Buehler, University College London
In her project Sarah will start a translational science methods club that brings together members of Turing, Roche as well as the wider academic but also clinical community to focus on how we can translate from data to science to clinic. This should foster discussion on how to deal with data, inference and the populations we study, addressing questions such as how to deal with different types of data, what inferences can be made from the methods we use and how we can better capture and benefit patient populations.
Kuniko Paxton, University of Hull
Kuniko’s project is creating and publishing an interview video series in which she will interview the researchers and collaborators in Turing-Roche Partnership. The researchers and collaborators are working together on the partnership North Star of ‘Generating insights into disease, patient, and outcome heterogeneity using advanced analytics’ which is a unique and advancing theme of delivering personalised and individually optimised treatment in healthcare. She surmises that because of this challenging theme, the researchers and collaborators experienced something interesting and special. Sharing these experiences and discoveries from being involved in the theme with researchers who are not directly involved is valuable. That is why the live opinions of researchers and collaborators at the forefront will provide a deep insight into the collaboration and give viewers a sense of closeness and realism that will intrigue them.
Syafiq Ramlee, University of Cambridge
Syafiq believes that creative solutions to the most complex of problems, especially in healthcare, lie in the intersections between fields. As a Turing-Roche Community Scholar, he brings a unique mix of experience: an academic history in engineering and biology, coupled with a personal affinity for graphic design work. He intends to integrate this diverse skill set by enacting a creative video campaign to raise awareness of the scientific interests of the Turing-Roche strategic partnership. He hopes to make science more accessible to, and digestible for, the wider community.
Zeena Shawa, University College London
As a Community Scholar Zeena aims to help develop a section on Data Missingness in the Turing Way handbook. Imputing and data missingness is an important aspect of a lot of research, due to missing data being a common problem, especially in large cross-cohort multimodal datasets. As a smaller side-project, this may be followed up with a relevant workshop or knowledge share session.
Davy Tennison, University College London
Davy and Florence will be working jointly to create a podcast for their community project. The theme of the podcast will be “Multi-modal data in healthcare” and will explore how different modalities can contribute to AI advancement in health, whilst looking at issues such as data representativeness.
Florence Townend, University College London
Florence and Davy will be working jointly to create a podcast for their community project. The theme of the podcast will be “Multi-modal data in healthcare” and will explore how different modalities can contribute to AI advancement in health, whilst looking at issues such as data representativeness.
Ellen Visscher, University of Oxford
Previously to her DPhil Ellen worked at a small software consultancy, where she developed an interest in coding practices and software development. Although she doesn’t claim to be an expert, this is an area that she think academia could improve. As such her community project aims to create a forum where researchers can share the tips and tricks that improve their coding workflow and productivity.
Xixuan Zhu, The Institute of Cancer Research
For the community project, Xixuan plans to produce a short film/documentary that focuses on the triangular relationship among patients, clinical trial teams, and translational researchers. The aim is to strengthen the connection among these three parties and make progress towards improving personalised clinical care.
