面向自主航运的智能海事态势感知与风险评估博士研究员
Intelligent maritime situational awareness and risk assessment for autonomous shipping
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
- 2027-01-20
- 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
- 本项目研究面向自主航运的智能海事态势感知与导航风险评估，利用自动识别系统（AIS）轨迹与视频数据研究船舶行为、交通交互、轨迹预测及不确定性风险评估。
- 申请条件
- 申请者需持有英国2:1荣誉学位或其国际同等学历，具备强有力的学术研究背景或先前研究经验者为佳。
- 待遇
- 提供竞争性资助机会（包括Presidential Bursaries和Horizon Europe学费减免等），涵盖学费及生活费津贴的具体形式依据竞争排名而定。
- 申请方式
- 通过南安普顿大学申请系统提交，选择研究型项目、2027/28学年、工程与物理科学学院、全职或兼职，搜索PhD Engineering & the Environment (7175)并添加导师姓名。
- 材料清单
- 简历（CV / resumé）
- 2份学术推荐信
- 至今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
- 2027-01-20
- 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）
- Dr Huanhuan Li
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-24
- 详情核验
判定依据（原文摘录）
- english_ok为true
English language qualification (if applicable)
原文
View all current projects
Postgraduate research project
Intelligent maritime situational awareness and risk assessment for autonomous shipping
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
20 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 understand complex maritime traffic and recognise emerging navigational risks? This project will investigate intelligent maritime situational awareness using Automatic Identification System (AIS) trajectories and video, focusing on vessel behaviour, traffic interactions, trajectory prediction and uncertainty-aware risk assessment to identify potentially hazardous situations in busy and constrained waterways.
Safe autonomous navigation depends on more than detecting surrounding vessels. Autonomous systems must understand how vessels are moving, anticipate their interactions and recognise situations that may develop into navigational hazards. Achieving reliable maritime situational awareness remains challenging, particularly in busy waterways where vessel behaviour is uncertain and traffic conditions change rapidly.
This project will investigate intelligent maritime situational awareness and navigational risk assessment for autonomous shipping, using Automatic Identification System (AIS) trajectories and video as complementary sources of maritime traffic information. The research will first examine how vessel observations can be integrated to reconstruct traffic situations and provide reliable information on vessel movements and interactions. It will then investigate methods for understanding vessel behaviour, predicting traffic developments and identifying potentially hazardous encounters, including crossing, overtaking and head-on situations.
A central research challenge will be to account for uncertainty in vessel behaviour, trajectory prediction and risk assessment. The project will explore how these uncertainties influence the identification and assessment of emerging navigational risks and the interpretation of evolving traffic situations.
Potential methods include computer vision, trajectory modelling, machine learning, probabilistic risk assessment and maritime traffic simulation. The research will focus on ports and constrained coastal waters, with evaluation using historical traffic data and representative navigation scenarios. The project will contribute to intelligent maritime situational awareness and risk-informed autonomous navigation, supporting the development of safer maritime autonomous surface ships and future maritime traffic management systems.
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).