Find a Data Champion

Leontien Talboom is a technical analyst in the digital preservation team, located at Cambridge University Library. Her role involves transferring data from digital carriers (optical discs, hard drives, floppy disks, etc.) to a more secure digital repository.

Marina has a PhD from the Chemical Engineering and Biotechnology Department at the University of Cambridge. She has previous industrial experience in R&D by working with multinational companies and start-ups. Currently, Marina is Commercialisation Associate in the Physical Sciences team at Cambridge Enterprise. She identifies and evaluates new technologies arising from University research, supporting academics with the protection of their intellectual property and commercialisation of their research outputs.

Prior to joining Cambridge Enterprise, Marina worked as a Research Analyst at the University of Cambridge. Amongst her main responsibilities, Marina conducted research and analysis of international projects and partnerships, providing analytical trends and insightful data that allowed the University to forge strategic partnerships with external institutions.

I'm a research fellow working to improve data management practices broadly across the materials and chemical sciences, with the aim to accelerate discovery and enable new data-driven approaches in the physical sciences. I lead the development of the decentralised open source RDM platform, datalab, used by several labs in Cambridge and beyond to track sample provenance, ingest raw characterisation data from instruments and easily disseminate data within and between labs. datalab has been designed primarily with materials chemistry and battery groups in mind, but has been extended to work for polymer research, direct air capture and autonomous labs. I also work extensively on API standardisation for crystal structure databases, via my involvement in OPTIMADE. I am very happy to discuss how people can engage with this work if they are in this domain, or how the approach could be adopted by other domains.

Before starting my current role, I completed my undergraduate studies in Theoretical Physics at the University of Manchester, after which I joined the University of Cambridge for an MPhil in Scientific Computing and subsequent PhD in Physics where I worked on crystal structure prediction for battery materials. I then joined UCLouvain in Belgium for a postdoc and research fellowship, before making my way back to Cambridge in 2025 as a Leverhulme Trust Early Career Research Fellow.

Qi received her PhD at the University of California, Los Angeles, where she developed computational methods to study alternative splicing and the evolution of HIV. Later she joined the UCLA Division of Dermatology to help identify the resistance mechanisms of targeted cancer therapies using computational tools. 
    
In 2011 she was awarded the Humboldt Research Fellowship to work in the Division of Theoretical Bioinformatics, and later the Division of Applied Bioinformatics, at the German Cancer Research Centre. There she worked on diverse bioinformatics projects with NGS data, such as studying genome-wide epigenetic regulation of cell differentiation, developing sequencing protocols and detecting somatic mutations from whole-genome sequencing data, as well as data integration and predictive modelling. 
    
Currently, she provides bioinformatics training and support to PhD students and postdoctoral researchers in the lab of Professor Beverley Glover.