Digital Intelligent Conservation and Adaptive Use of Urban and Rural Heritage

About the Project

Our project investigates how artificial intelligence and digital intelligence technologies can advance the conservation and adaptive reuse of urban and rural heritage in China. Focusing on vulnerable traditional settlements, large archaeological landscapes, and heritage districts, the research explores how AI, deep learning, and digital twins can be used to identify resilience patterns, analyse environmental and socio-spatial risks, and support evidence-based conservation and development strategies.

Our project aims to develop data-driven frameworks that integrate multi-source information, including spatial data, environmental sensing, heritage documentation, and socio-economic indicators, into intelligent digital models. These models will enable continuous monitoring of heritage environments, simulation of future scenarios, and assessment of conservation and adaptive-use interventions. Rather than treating heritage as static objects, the research conceptualises urban and rural heritage as dynamic socio-ecological systems shaped by culture, environment, technology, and economic change.

You will work with advanced methods in AI, machine learning, spatial computing, and digital twin modelling, while engaging with real heritage sites and applied research contexts. The project will deliver both practical digital tools and new theoretical insights for smart heritage conservation, resilient settlement planning, and sustainable revitalisation.

Joint Supervisory Team:

• XJTLU supervisor: Professor Dr Marc Aurel Schnabel
• XJTU supervisor: Professor Dr Binqing Zhai
• UoL supervisor: Dr Guzden Varinlioglu

Requirements:

A UK first-class or upper second-class honours Bachelor's degree and a UK Master's degree with Merit (or their equivalent) are required for PhD admissions. Exceptional candidates holding only a Bachelor's degree may be considered on an individual basis.

Evidence of good spoken and written English is essential. The candidate should have an IELTS (or equivalent) score of 6.5 or above, if the first language is not English.

For more information about entry requirements and admission procedures of PhD programme at XJTLU, please visit:

Entry Requirement - Xi'an Jiaotong-Liverpool University

How to Apply - Xi'an Jiaotong-Liverpool University

Other Requirements:

You are a highly motivated candidate with strong academic potential and a clear interest in pursuing high-level, interdisciplinary doctoral research, with a background in architecture, urban studies, digital heritage, computer science, data science, or related fields. Experience with AI, machine learning, GIS, computational design, or digital modelling is highly valued, together with strong analytical ability and academic writing skills.

Programme Structure:

Doctoral students in the joint programme are registered with both XJTLU and the UoL. Upon successful completion of the programme, the students will be awarded a PhD degree from University of Liverpool.

During their doctoral studies at XJTLU, students are expected to conduct research at XJTU as visiting students. Additionally, students have the opportunity to apply for a three to six-month research visit to UoL.

How to Apply:

Interested applicants are advised to email MarcAurel.Schnabel@xjtlu.edu.cn the following documents for initial review and assessment (Please include the project title in the subject line).

• CV
• Two formal reference letters
• Personal statement outlining your interest in the position
• Certificates of English language qualifications (IELTS or equivalent)
• Full academic transcripts in both Chinese and English (for international students, only the English version is required)
• Verified certificates of education qualifications in both Chinese and English (for international students, only the English version is required)
• PDF copy of Master Degree dissertation (or an equivalent writing sample) and examiners reports available