Data Champions Search

Amelie Roper is Research Facilitator at Cambridge University Library. Her role involves supporting grant applications for research funding for library activities, and assisting with project delivery once funding is awarded. 

She studied music at King’s College London and Library and Information Studies at University College London. She also holds a PhD in book history from the University of St Andrews. 

Her research interests include early modern European print culture, digital music publishing and big data.

My interests lie in the ideation, innovation and translation processes for healthcare technologies in resource-limited settings. I am a Postdoctoral Research Associate in the International Health Systems Group (IHSG), Department of Engineering, funded by the NIHR Global Health Research Group on Acquired Brain and Spine Injury.

In my role as Academic Services Librarian, I manage services delivered in the Haddon Library with a specific focus on supporting teaching and research for the Departments of Archaeology and Social Anthropology. I am also the Research Support Lead for the Humanities and Social Sciences Libraries Team, working across the School of HSS to support research excellence and training as well as assisting in exercises such as the REF.

Additional areas of expertise: Information literacy, Research communication, Public engagement, Creative Commons, Open sharing.

As the Research Support Librarian at the Department of Engineering I am part of the Technology Libraries team providing library services for the Departments of Engineering, Chemical Engineering and Biotechnology, and Computer Science and Technology. My role includes providing training and advice on research data management and open data. I became a Data Champion in my previous role as the Library Manager at the Cambridge Conservation Initiative, supporting nature conservation researchers from the university and NGOs. I have previous experience, from research during masters degrees, working with ethnographic data in libraries and statistical analysis of palaeobiology data using R.