先进数值建模与埋地基础设施预测性维护博士研究员
PhD Studentship in Advanced Numerical Modelling and Predictive Maintenance of Buried Infrastructure
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
AI 中文速览
- 研究内容
- 本项目将开发一个混合物理与数据驱动的框架，用于评估埋地基础设施的状况并预测其性能，重点关注供水管道及相关的地面不稳定性。研究将创新计算建模技术，以模拟结构损伤、漏水、土壤侵蚀和地面变形之间的相互作用，并研究人工智能辅助的代理模型和数据同化，将数值预测与监测观测结合起来。
- 申请条件
- 申请人应持有土木工程、岩土工程、机械工程、应用数学、计算机科学或紧密相关学科的一等或二等荣誉学士学位（或同等学历），相关硕士学位或研究/行业经验将是一个优势。需具备较强的分析和数学能力，对计算力学和数值建模感兴趣，并具备使用Python或C++等语言进行编程或科学计算的经验，以及良好的书面和口头沟通能力。
- 待遇
- 资助涵盖3.5年期项目的学费（英国/本土学生标准）以及英国研究与创新署（UKRI）最低年度生活补助（目前为每年21,805英镑）。国际学生若愿意通过自筹资金或外部来源（如英联邦奖学金、斯伦贝谢基金会或国家留学基金委资助）支付本土与国际学费之间的差额，则欢迎申请。
- 申请方式
- 感兴趣的候选人应通过电子邮件联系Dr Ruofeng Feng (r.feng@bham.ac.uk)，邮件主题为“PhD studentship + [您的姓名] + [当前机构] + [当前学习项目]”。邮件中需包含两位推荐人的姓名和联系方式，并附上规定材料。
- 材料清单
- 简历 (CV)
- 支持声明（最多两页）
- 已获及进行中大学学历的学术成绩单
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 截止
- （Europe/London） 剩 90 天
- 学科
- 工程
- 合同类型
- 雇佣合同
- 原文薪资
- GBP 21,805 / 年（税前）
- 税后月薪（估）
- ¥13,700；房租后 ¥5,400
- 估算假设
- 单身、无子女、雇佣合同的粗略估算，以学校 offer 为准；扣除率 18%；汇率日期 2026-10-01
- 原帖发布
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Ruofeng Feng
- 来源
- jobs.ac.uk（英国博士项目及学术招聘） · 最近核对 2026-10-20
- 详情核验
判定依据（原文摘录）
- 确认该岗位为博士培养机会
This PhD project will develop a hybrid physics-based and data-driven framework for assessing the condition and predicting the performance of buried infrastructure
- 确认工作语言为英语（无其他本地语言要求）
Good written and verbal communication skills.
- 确认要求至少本科学位而非仅限学士直读
A First- or Upper Second-class Honours degree, or an equivalent qualification, in civil engineering, geotechnical engineering, mechanical engineering, applied mathematics, computer science or a closely related discipline. A relevant master’s degree and/or research or industry experience would be an
原文
Buried infrastructure underpins essential urban services, yet its deterioration often remains hidden until significant damage or service disruption occurs. Ageing pipelines face increasing pressures from climate change, groundwater fluctuations and nearby construction. Their integrity is closely linked to the surrounding ground. Pipe defects can initiate water leakage and internal soil erosion, leading to loss of support, subsidence and potentially sinkhole formation. Conversely, ground movement can impose additional stresses on pipelines, accelerating damage and leakage. Understanding and predicting this dynamic, coupled deterioration process is essential for timely and effective maintenance.
This PhD project will develop a hybrid physics-based and data-driven framework for assessing the condition and predicting the performance of buried infrastructure, with a focus on water pipelines and associated ground instability. The central research question is how advanced computational models and monitoring data can be combined to identify infrastructure deterioration and predict its progression towards failure.
The project will innovate computational modelling techniques to simulate interactions between structure damage, water leakage, soil erosion and ground deformation. Building on these physical models, the research will investigate AI-assisted surrogate modelling and data assimilation to connect numerical predictions with monitoring observations, potentially including distributed fibre-optic strain measurements, hydraulic data and ground displacement. The anticipated outcome is a validated computational framework linking deterioration mechanisms, monitoring-informed prediction and maintenance decision-making. The project will support earlier intervention, reduced water losses and service disruption, and greater resilience of buried infrastructure to urban ground hazards.
The successful candidate will be based in the School of Engineering at the University of Birmingham, which hosts the National Buried Infrastructure Facility (NBIF, www.birmingham.ac.uk/nbif ). They will have access to advice and support from a multidisciplinary team of experts in numerical modelling, AI-solutions, physical sensing for buried infrastructure, alongside documented experimental datasets obtained using a wide range of instrumentation and measurement techniques, including fibre-optic sensing, laser scanning, and force and strain measurements.
This project is expected to start before/in September 2027.
Requirements: The successful candidate will be motivated and enthusiastic about working across disciplines to address challenges in buried infrastructure resilience. Applicants should have:
• A First- or Upper Second-class Honours degree, or an equivalent qualification, in civil engineering, geotechnical engineering, mechanical engineering, applied mathematics, computer science or a closely related discipline. A relevant master’s degree and/or research or industry experience would be an advantage.
• Strong analytical and mathematical skills, with an interest in computational mechanics and numerical modelling.
• Experience in programming or scientific computing using languages such as Python, and C++.
• Good written and verbal communication skills.
Funding notes:
Funding for this project covers tuition fees (UK/home-student rate), UKRI minimum annual stipend (currently £21,805/annum) for the full duration of the 3.5-year programme. International students are welcome to apply if you are willing to cover the tuition difference between home and international rates through self-funding or external sources. Support will be provided for applications for external funding, such as Commonwealth fellowships or funding from the Schlumberger Foundation and the China Scholarship Council.
Interested candidates should email Dr Ruofeng Feng at r.feng@bham.ac.uk via the above ' Apply ' button using the subject line “PhD studentship + [Your name] + [Current institution] + [Current programme of study]”. Please include the names and contact details of two referees in the email. Attach the following documents:
• Your CV.
• A supporting statement (maximum two pages).
• Academic transcripts for awarded and in-progress university qualifications.
£21,805 per annum