AI低碳混凝土材料与结构设计博士研究员
AI for low-carbon concrete materials and structural design
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。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • cover letter explaining your motivation and suitability for the project • research proposal (1 or 2 pages) • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-08-31
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.
- 资助条件
- 原帖为竞争性或附条件资助说明，未确认本项目获资助及申请人能获奖；不作为保证全奖。
- 原帖材料说明
- • cover letter explaining your motivation and suitability for the project
- • research proposal (1 or 2 pages)
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目将混凝土材料开发与结构设计相结合，旨在减少碳排放的同时满足工程要求。研究将结合机器学习、结构分析与优化，探讨混凝土性能、构件尺寸及配筋对性能和隐含碳的影响，开发有助于工程师实现更可持续混凝土施工的AI辅助方法。
- 申请条件
- 申请人必须持有英国2:1荣誉学位或国际同等学历，专业背景包括土木或结构工程、材料科学、计算机科学、数学或相关学科。具备Python、MATLAB或同类语言编程经验、混凝土材料、结构分析或机器学习知识、数值建模、优化或碳评估经验者优先。
- 待遇
- 学校为英国及国际学生提供一系列资助机会，竞争性总统奖学金可为顶级申请者涵盖海外学费与英国学费之间的差额，院系提供的竞争性学生奖学金通常涵盖英国本土学费及生活费津贴。具体薪资待遇与合同类型原文未详细说明。
- 申请方式
- 申请人需选择研究型项目类型、2027/28学年、工程与物理科学学院，选择全职或兼职，搜索PhD Engineering & the Environment (7175)项目，并在申请表第二部分添加导师姓名。
- 材料清单
- 说明动机与项目适切性的求职信（cover letter）
- 研究计划书（1或2页）
- 个人简历（CV）
- 2封学术推荐信
- 迄今为止的学位成绩单与证书
- 英语语言资格证明（如适用）
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2027-08-31
- 学科
- 材料科学
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Ye Li
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- english_ok
Applicants whose first language is not English must meet the University's English language requirements.
- bachelor_ok
You must have a UK 2:1 honours degree, or its international equivalent
原文
View all current projects
Postgraduate research project
AI for low-carbon concrete materials and structural design
Funding
Competition funded
Competition funded
View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
31 Aug 2027
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
This project connects concrete material development and structural design to reduce carbon emissions while meeting engineering requirements. Combining machine learning, structural analysis and optimisation, the research will investigate how concrete properties, member dimensions and reinforcement influence performance and embodied carbon, helping engineers identify efficient designs for more sustainable concrete construction.
Reducing the carbon footprint of concrete construction requires decisions about both materials and structures. A concrete mix with lower emissions per cubic metre may require a larger member or more reinforcement to carry the same load. Understanding these interactions is essential to identify designs that reduce emissions while meeting engineering requirements.
This project will develop an AI-assisted approach that links concrete composition, mechanical properties and structural design. You'll build machine learning models to predict strength and stiffness, then connect these predictions to the behaviour of selected reinforced concrete members. Structural calculations will establish whether each design can carry the required loads and limit deformation during use. You'll also examine how uncertainty in material properties and emission estimates affects design choices.
The research will estimate embodied carbon from the quantities of concrete and reinforcement and their associated production emissions. An optimisation method will search for designs that lower emissions while satisfying the specified performance requirements. You'll investigate how changing material choices, member dimensions or design demands affects the available carbon savings. Predictions will be assessed against independent experimental data and structural calculations, with conventional designs providing a benchmark. The outcome will be an approach that helps engineers make informed material and design choices.
You will:
• develop practical skills in machine learning, concrete engineering and structural optimisation
• learn to assess carbon emissions alongside structural performance through realistic design problems
• build research and programming experience relevant to engineering consultancy, construction innovation and academic careers
You'll receive training in Python, machine learning, concrete mechanics and structural analysis. You'll learn how to estimate embodied carbon, search for designs that meet specified requirements, and evaluate predictions against data and engineering calculations. Training will also cover how uncertainty in material properties and emission factors affects design decisions. Professional development will support research planning, scientific writing, presentations and reproducible programming. You'll gain experience explaining the relationship between material choices, structural performance and carbon emissions to engineering audiences.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Dr Ye Li
PhD
Lecturer
Research interests
• High-Performance Marine Concrete
• Sustainable Cementitious Material and Concrete
• Fire Resistance of Concrete Materials and Structures
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent, in one of the following:
• civil or structural engineering
• materials science
• computer science
• mathematics
• a related discipline
Essential skills:
• an interest in applying AI to concrete materials and structural design, and a willingness to learn across disciplines
• ability to work independently, communicate clearly and collaborate effectively
Desirable skills:
• programming experience in Python, MATLAB or a comparable language
• knowledge of concrete materials, structural analysis or machine learning
• experience with numerical modelling, optimisation or carbon assessment
• research experience and clear scientific writing
Applicants whose first language is not English must meet the University's English language requirements.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• cover letter explaining your motivation and suitability for the project
• research proposal (1 or 2 pages)
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, please email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Ye Li (Ye.Li@soton.ac.uk).