Dynamic risk intelligence for safe autonomous shipping under changing operational conditions 博士研究员
Dynamic risk intelligence for safe autonomous shipping under changing operational conditions
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: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-01-10
- 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
- • 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
- 本项目旨在开发动态风险智能方法，以评估不断变化的运行条件下的自主船安全边界，识别演变中的风险状态，并支持关于继续运行、降级、应急和后备方案的可解释决策。
- 申请条件
- 申请者需拥有英国2:1荣誉学士学位或国际同等学历，具备强有力的学术研究背景或先前的研究经验者优先。
- 待遇
- 学校为英国及国际学生提供一系列资助机会，包括竞争性总统奖学金和学院提供的学费及生活费资助奖学金，具体取决于择优评定。
- 申请方式
- 申请人需通过学校在线系统申请，选择研究型项目、2027/28学年、工程与物理科学学院，搜索“PhD Engineering & the Environment (7175)”项目，并在申请表第二部分添加导师姓名。截止日期为2027年1月10日。
- 材料清单
- 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
- 2027-01-10
- 学科
- 工程
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Huanhuan Li
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-17
- 详情核验
判定依据（原文摘录）
- is_phd为true
Type of degree Doctor of Philosophy
- bachelor_ok为false
Entry requirements 2:1 honours degree
原文
View all current projects
Postgraduate research project
Dynamic risk intelligence for safe autonomous shipping under changing operational conditions
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
10 Jan 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
How can autonomous ships recognise when changing traffic, environmental or system conditions make continued autonomous operation unsafe? This project will develop dynamic risk intelligence methods to assess operational conditions against autonomous ship capability boundaries, identify evolving risk states, and support explainable decisions on continued operation, degradation, fallback and contingency.
Maritime autonomous surface ships must operate safely in environments that change continuously. Traffic density, weather, visibility, communication availability, sensor performance and autonomous system capability can all affect whether an autonomous ship or individual autonomous function remains able to operate safely. A key challenge is therefore to determine when autonomous operation can continue and when intervention, degradation or fallback becomes necessary.
This project will develop dynamic risk intelligence methods for safe autonomous shipping. The research will investigate how Operational Envelopes (OEs) and Operational Design Domains (ODDs) can be represented as capability boundaries for autonomous ships and their functions, and how changing operational conditions can be assessed against these boundaries.
The project will develop methods for modelling the relationships between operational conditions, autonomous functions, vessel interactions and navigational risk. Particular attention will be given to uncertainty and dynamic risk evolution, including transitions between normal, degraded, fallback-required and contingency-required operating states. Potential approaches include probabilistic risk modelling, Bayesian Networks, Dynamic Bayesian Networks, system-theoretic safety analysis and data-driven methods.
The research will also investigate how dynamic risk assessment can be translated into explainable operational information to support decisions such as continued autonomous operation, increased safety margins, function degradation, remote supervision, mode switching and fallback. The proposed methods will be evaluated using representative autonomous navigation scenarios, historical maritime traffic data and simulation-generated scenarios. The research will contribute to risk-aware autonomous navigation and provide methods supporting the safety assurance and future deployment of Maritime Autonomous Surface Ships.
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 Huanhuan Li
PhD (Eng.), FHEA
Lecturer in Maritime Engineering
Research interests
• Maritime safety and security
• AI-driven autonomous shipping
• Decarbonisation and green shipping
Entry requirements
A UK 2:1 honours degree, or its international equivalent.
A strong academic research background or previous research experience is desirable.
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:
• 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, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Huanhuan Li (Huanhuan.Li@soton.ac.uk).