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西交利物浦大学/招博士研究生
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项目课题：城市和乡村遗产的数字化智能保护和适应性利用digital intelligent conservation and adaptive use of urban and rural heritage 项目编号：sfxjtu2536 brief introduction of the three supervisors 导师简介 professor marc aurel schnabel (xjtlu) is an internationally recognised academic leader with extensive global research leadershipand in digital architecture, ai-augmented design, immersive environments, and smart heritage. as dean of the design school at xi’an jiaotong-liverpool university, he leads major interdisciplinary initiatives across ai, digital twins, xr, and cultural heritage, with over 270 publications and extensive global research collaborations. professor binqing zhai (xjtu) is head of architecture, and director of the institute of architecture at xi’an jiaotong university. his research focuses on traditional settlements, social-ecological resilience, risk assessment, and sustainable conservation strategies, with strong expertise in heritage protection in mountainous and rural regions. dr guzden varinlioglu (university of liverpool) is an architect and computational design scholar specialising in immersive technologies, digital cultural heritage, and ai-supported design workflows. with international research experience at mit, ucla, and texas a&m, she brings strong strengths in computational methods, digital heritage, and design research. 马尔克·奥雷尔·施纳贝尔教授（西交利物浦大学）**是国际知名的数字建筑与智能设计领域学者，研究聚焦人工智能、沉浸式环境、数字孪生与智慧遗产。作为西交利物浦大学设计学院院长，他主持多项跨学科科研计划，拥有270余项学术成果及广泛国际合作网络。 翟斌清教授（西安交通大学）**为建筑学系主任、建筑研究所所长，长期从事传统聚落保护、社会—生态韧性、风险评估与可持续发展研究，在中国山区与乡村遗产保护领域具有深厚学术与实践基础。 古兹登·瓦林里奥卢博士（利物浦大学）**是计算性设计与数字文化遗产方向建筑师，研究涵盖沉浸式技术、计算设计与ai辅助设计流程，曾在mit、ucla、德州农工大学开展研究，具备扎实的数字遗产与设计计算专长。 key aspect/summary of research project项目简介 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 develop an internationally competitive research profile by working 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. 本博士研究项目聚焦人工智能与数字智能技术如何推动中国城乡遗产的保护与适应性利用。 研究以脆弱传统聚落、大型考古遗址及历史文化片区为对象，探讨如何通过人工智能、深度学习与数字孪生技术识别韧性特征、分析环境与社会空间风险，并支撑科学化、智能化的遗产保护与发展决策。 项目旨在构建数据驱动的研究框架，整合空间信息、环境监测、遗产档案与社会经济数据，形成智能数字模型，实现遗产环境的持续监测、情景模拟与保护及活化策略评估。本研究突破将遗产视为“静态对象”的传统范式，把城乡遗产理解为由文化、环境、技术与经济共同塑造的动态社会—生态系统。 博士研究将结合人工智能、机器学习、空间计算与数字孪生建模方法，并依托真实遗产场景与应用案例展开。项目将产出面向实践的数字工具与具有国际前沿价值的理论成果，为智能遗产保护、韧性聚落规划与可持续更新提供方法支撑与决策依据。 other preferred qualification and skill set of the candidate 对项目候选人的其他学术背景及技能要求 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. 你应具备扎实的研究动机与学术潜力，拥有建筑、城乡规划、数字遗产、计算机科学、数据科学或相关背景。具备人工智能、机器学习、gis、计算设计或数字建模经验者优先，同时应具备良好的分析能力与学术写作能力。 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. this position is open to all qualified candidates irrespective of nationality. 参加联合培养博士项目的学生将同时在西交利物浦大学（xjtlu）和利物浦大学（uol）注册。顺利完成该项目后，学生将被授予利物浦大学的博士学位。 在西交利物浦大学攻读博士学位期间，学生需以访问学生身份在西安交通大学（xjtu）开展研究工作。此外，学生还有机会申请为期三至六个月的利物浦大学研究访问。该职位面向所有符合资格的候选人开放，不限国籍。 有意者请将个人简历及其他有助于申请的材料发送至marcaurel.schnabel@xjtlu.edu.cn 注: 不用跟帖，直接发邮件就行，主题请注明博士申请 |
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2026-09-01 16:38:43, 272.54 K
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