Moving the Frame: New Computational Practices for the BT Film Collection
Leverage advances in machine learning and computer vision to transform metadata creation for heritage film archives. Develop innovative, reusable computational tools that enhance archival discoverability and research.
AI-generated overview
Project Description
Entry Requirements
Applicants must be able to demonstrate an interest in archives and digital cultural heritage and the potential and enthusiasm for developing their technical skills in related areas.
UCL and BTGA are keen to encourage the widest range of potential students to study for this studentship. We particularly welcome applications from people of Global Majority backgrounds as they are currently underrepresented in doctoral student cohorts.
How to Apply
Prepare your documents
You need to get these ready:
CV
Academic transcripts
Personal statement / cover letter
Research proposal (if requested by UCL portal)
Proof of English
Visit the website for more information
Eligibility
Supervisor Profile
Dr Daniel Wilson and Prof Andrew Flinn are scholars at UCL’s Department of Information Studies, focusing on digital humanities, archival studies, and AI applications in cultural heritage. They lead interdisciplinary research that combines theory and practice to innovate in knowledge organisation and digital asset management. Their work is internationally recognized for advancing new methods in archival science and information studies.