多模态学习与传感器融合用于视觉和水下声学船舶监测博士研究员
Multimodal learning and sensor fusion for vessel monitoring using vision and underwater acoustics
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
- 2027-01-15
- 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
- 本项目研究如何结合水下声音和岸基视觉来更有效地监测船舶，探索机器学习和多模态融合技术，以改善河流和沿海水域中的船舶检测、表征与追踪，并利用视觉获得的知识增强声学监测。
- 申请条件
- 申请人需持有英国 2:1 荣誉学士学位或其国际同等学历；具备相关领域的先前研究经验（通过研究项目、毕业论文或同行评审出版物证明）为加分项。
- 待遇
- 学校为英国本土及国际学生提供一系列资助机会，包括竞争性总统奖学金（Presidential Bursaries）及学院提供的竞争性奖学金（通常涵盖英国本土学费及生活津贴），具体奖学金名额基于竞争择优发放。
- 申请方式
- 申请人需在线提交申请，选择项目类型为研究型（Research）、2027/28学年、工程与物理科学学院，选择全职或兼职，搜索项目 PhD Engineering & the Environment (7175)，并在申请表第二部分添加导师姓名。
- 材料清单
- 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
- 2027-01-15
- 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 William Wu, Dr Huanhuan Li, Professor Paul White
- 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）
- bachelor_ok
A UK 2:1 honours degree, or its international equivalent.
原文
View all current projects
Postgraduate research project
Multimodal learning and sensor fusion for vessel monitoring using vision and underwater acoustics
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
15 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 underwater sound and shore-based vision work together to monitor vessels more effectively? This PhD explores machine learning and multimodal fusion to improve vessel detection, characterisation and tracking in rivers and coastal waters, and to enhance acoustic monitoring using knowledge gained from vision when cameras can no longer observe.
Cameras provide information about vessel positions, sizes, types, numbers, speeds and directions of travel. Underwater sound provides complementary evidence beyond camera coverage and when visual observations are unreliable. How can these modalities improve maritime monitoring together, and how can visual knowledge strengthen acoustic monitoring?
You will develop machine learning and sensor fusion methods combining hydrophone arrays, shore-based cameras and, where available, Automatic Identification System (AIS) data. The research will investigate when multimodal sensing outperforms individual modalities, how knowledge and prior information gained from multimodal observations can enhance acoustic-only monitoring, and how uncertainty associated with each modality can inform vessel localisation and tracking.
Potential approaches include cross-modal representation learning, knowledge transfer between modalities, uncertainty-aware fusion, and probabilistic tracking informed by vessel characteristics and motion. Particular attention will be given to associating acoustic and visual observations and maintaining robust monitoring as sensing conditions and sensor availability change.
Initial studies will focus on rivers and constrained coastal navigation routes, using known sensor locations and waterway geometry to support acoustic localisation. Multimodal, vision-only and acoustic-only approaches will be evaluated for vessel detection, characterisation and tracking, testing robustness to degraded sensing and missing modalities, and generalisation to previously unseen vessels.
You will build on an existing field dataset, with hydrophone arrays, cameras and the University of Southampton’s Iridis high-performance computing facilities available. Further field measurements can extend the dataset. The supervisory team brings complementary expertise in underwater acoustics, signal processing and maritime engineering, supporting research with applications in waterway management and future autonomous vessel operations.
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 William Wu
BEng, MSc, PhD
Senior Teaching Fellow
Research interests
• Underwater acoustics
• Signal processing
• Fibre optic acoustic sensing
Supervisors
Dr Huanhuan Li
PhD (Eng.), FHEA
Lecturer in Maritime Engineering
Research interests
• Maritime safety and security
• AI-driven autonomous shipping
• Decarbonisation and green shipping
Professor Paul White
Professor of Statistical Signal Processing
Research interests
• Signal processing
• Underwater acoustics and bioacoustics (the way animals, especially marine mammals, use sound)
• The processing of calls of marine mammals
Entry requirements
A UK 2:1 honours degree, or its international equivalent.
Previous research experience in a relevant area, demonstrated through a research project, dissertation or peer-reviewed publication, 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 William Wu (William.Wu@soton.ac.uk).