Haida Liang
6 months ago
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AI-Aided Data-Driven Study of Historical Parchments: Making, Degradation, and Origin Nottingham Trent University in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Funded PhD Project (Students Worldwide)
Deadline
Expired
Country
United Kingdom
University
University of Nottingham
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Keywords
About this position
This PhD project offers a unique opportunity to explore the making, degradation, and origin of historical parchments using advanced AI-aided, data-driven approaches. Parchments, made from treated animal skins, have served as the primary writing material in Europe and West Asia from the 4th to the 15th century, preserving invaluable records of civilisation. Understanding their origin, manufacturing processes, and degradation mechanisms is crucial for heritage conservation and manuscript dating.
The research will focus on the identification of animal species (calf, sheep, goat) used in parchment production, leveraging biocodicology and both invasive (ZooMS, eZooMS) and non-invasive (reflectance spectroscopy, hyperspectral imaging, optical coherence tomography) analytical techniques. Machine learning and AI methods will be developed to enhance species identification and to disentangle complex multimodal imaging data, capturing information about animal origin, age, manufacturing differences, and degradation states.
Students will work with a large collection of parchment manuscripts, employing non-invasive imaging to record statistical variations and train robust AI models. Comparative studies will be conducted on manuscripts from Belgium and British archives, representing different manufacturing traditions and exposure conditions. Reference proteomics analyses will be used for verification and calibration.
The project is based in the Imaging and Sensing for Archaeology, Art history and Conservation (ISAAC) Lab at Nottingham Trent University and the Artificial Intelligence for Cultural Heritage (PHOENIX) collaborative research project at the University of Namur, Belgium. The studentship is jointly funded by both institutions, covering tuition fees and stipend, and the successful candidate will be registered at both universities.
Applicants should have a background in physical sciences or bioinformatics, with a strong interest in heritage science, conservation, and archaeological science. The project welcomes candidates from diverse backgrounds and encourages applications from underrepresented communities. The research environment is inclusive and supportive, offering access to cutting-edge facilities and interdisciplinary expertise.
Application deadline is June 15, 2026. For further information, visit the ISAAC Lab and PHOENIX project websites, or contact the supervisory team. Apply via the Nottingham Trent University applications page, ensuring you meet the eligibility criteria.
Funding details
Funded PhD Project (Students Worldwide)
What's required
Applicants should have a background in physical sciences or bioinformatics and demonstrate interest in heritage science, conservation science, or archaeological science. Motivation and relevant skills in machine learning, analytical chemistry, and imaging techniques are desirable. Eligibility criteria are outlined on the applications page. No specific GPA or language test requirements are mentioned.
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Professors
Professor at School of Science & Technology
United Kingdom
Research Interests
Mineralogy
Archaeometry
Optical Imaging
Hyperspectral Imaging
Time-resolved Spectroscopy
Professor at School of Science & Technology
United Kingdom
Research Interests
Analytical Chemistry
Statistics
Machine Learning
Optical Coherence Tomography
Archaeology
Professor at School of Science & Technology
United Kingdom
Research Interests
Conservation Biology
Statistics
Machine Learning
Experimental Physics
Materials Science
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.