Digital Intelligent Conservation and Adaptive Use of Urban and Rural Heritage

This PhD opportunity at Xi’an Jiaotong-Liverpool University focuses on the digital intelligent conservation and adaptive use of urban and rural heritage in China. The project investigates how artificial intelligence, machine learning, and digital intelligence technologies can advance the preservation and revitalisation of vulnerable traditional settlements, archaeological landscapes, and heritage districts. By leveraging AI, deep learning, and digital twin modelling, the research aims to identify resilience patterns, analyse environmental and socio-spatial risks, and support evidence-based conservation and development strategies. Doctoral candidates will develop data-driven frameworks that integrate 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. The project conceptualises urban and rural heritage as dynamic socio-ecological systems shaped by culture, environment, technology, and economic change, moving beyond the traditional view of heritage as static objects. Students will work with advanced methods in AI, machine learning, spatial computing, and digital twin modelling, engaging with real heritage sites and applied research contexts. The research delivers practical digital tools and theoretical insights for smart heritage conservation, resilient settlement planning, and sustainable revitalisation. The joint supervisory team includes Professor Dr Marc Aurel Schnabel (XJTLU), Professor Dr Binqing Zhai (XJTU), and Dr Guzden Varinlioglu (UoL), providing interdisciplinary guidance and international collaboration. Applicants must have a UK first-class or upper second-class honours Bachelor's degree and a UK Master's degree with Merit (or their equivalent). Exceptional candidates with only a Bachelor's degree may be considered. Strong English proficiency is required (IELTS 6.5 or above if applicable). Ideal candidates are highly motivated, with academic potential and a clear interest in interdisciplinary doctoral research, and 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, along with strong analytical and academic writing skills. The programme structure involves registration with both XJTLU and the University of Liverpool, with the PhD degree awarded by the University of Liverpool upon completion. Students are expected to conduct research at XJTU as visiting students and may apply for a three to six-month research visit to UoL. Applications are accepted year round. For initial review, applicants should email Professor Schnabel with the required documents, including CV, reference letters, personal statement, English language certificates, academic transcripts, verified certificates, and a writing sample. For further information, visit the project link or contact the supervisor directly.