机器人监测与水下动态环境变化检测博士研究员（MSCA BlueOcean 博士网络）
PhD Studentship: Marie Sklodowska-Curie Actions Doctoral Network BlueOcean
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
- 本项目旨在开发新颖的机器人监测和数据处理方法，以在大空间尺度上记录动态海底环境的变化。研究内容结合先进的机器人定位、高分辨率测绘方法与高级机器学习特征检测，实现重复水下调查中演变海底场景的稳健对齐，并开发概率模型来检测噪声和不确定性下的微妙变化。
- 申请条件
- 候选人必须在招募之日未获得博士学位；可以是任何国籍；在招募之日前36个月内，在英国居住或开展主要活动（工作、学习等）的时间不得超过12个月。
- 待遇
- 全职固定期限36个月。年薪为 43,994 至 47,279 英镑（根据汇率每半年调整一次）。大学提供慷慨的产假政策、校内托儿设施以及促进员工福祉和工作生活平衡的各种福利。
- 申请方式
- 请通过指定的申请链接提交申请。详情可参考职位描述和人员规范说明。
- 材料清单
- 简历 (Curriculum Vitae)
- 两封推荐信 (Two reference letters)
- 迄今为止的学位成绩单/证书 (Degree Transcripts/Certificates to date)
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 24 天
- 学科
- 工程
- 合同类型
- 雇佣合同
- 合同期限
- 36 个月
- 原文薪资
- GBP 43,994–47,279 / 年（税前）
- 税后月薪（估）
- ¥27,700–¥29,700；房租后 ¥19,400–¥21,400
- 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
- 来源
- jobs.ac.uk（英国博士项目及学术招聘） · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- 这是一项博士培养机会
This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales.
- 属于 MSCA 博士网络且有资助
You will be part of the EU-funded BlueOcean Marie Skłodowska-Curie Doctoral Network, working alongside 13 PhD researchers across leading European institutions.
- 国际申请者可申，但受MSCA居住地限制
• can be of any nationality • must not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 36 months immediately before their recruitment date.
原文
Full-Time Fixed-Term for 36 months
This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales.
Motivation: Understanding how the seafloor evolves is critical for environmental monitoring and subsea infrastructure inspection. Natural processes and human activities drive changes over time, yet detecting these reliably remains challenging. Improved methods could enable early identification of risks to ecosystems and infrastructure, while providing quantitative evidence to support effective intervention and adaptive management.
Challenges: Documenting change in GNSS-denied subsea environments presents significant challenges. While changes occur over large spatial scales, change is often gradual, meaning that between seasonal or yearly deployments, the magnitude of change at any point on the seafloor remains below to the detection limit of even high-resolution mapping sensors. In addition, recognising and aligning scenes across repeated surveys is difficult due to navigation drift, evolving scene structure, and sensitivity to environmental conditions.
Research questions:
• How can evolving seafloor scenes be consistently recognised and spatially aligned across repeated subsea surveys in GNSS-denied environments?
• How can small seafloor changes be reliably detected when they are comparable to sensor noise?
• How can full-field uncertainty be modelled and propagated to support large-scale change analysis?
Approach: You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature detection to enable evolving subsea scenes to be robustly aligned across repeat surveys. You will develop probabilistic models to detect subtle changes under noise and uncertainty. Your work will be validated using simulation, existing datasets from the University of Southampton’s Smarty200 AUV, and new data collected during field campaigns with the Ocean Perception group. Controlled experiments will also be conducted in the Maritime Robotics and Instrumentation Laboratory and its dedicated 8x8x6m deep-water tank.
Training and Environment: You will be part of the EU-funded BlueOcean Marie Skłodowska-Curie Doctoral Network, working alongside 13 PhD researchers across leading European institutions. The programme provides interdisciplinary training in robotics, sensing, and AI for marine monitoring, as well as access to internationally recognised experts and industry partners. You will also undertake up to two three-month secondments with organisations including CNR (Italy) and Voyis Imaging (Canada).
Eligibility:
This PhD is funded via the European Commission. Recruitment is taking place following the
European Code of Conduct for Recruitment of Researchers .
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.
The candidate:
• must not have a doctoral degree at the date of their recruitment
• can be of any nationality
• must not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 36 months immediately before their recruitment date.
To apply, please provide:
• Curriculum Vitae
• Two reference letters
• Degree Transcripts/Certificates to date
If you are applying for this role, you must also apply for the PhD below.
https://www.phdscanner.com/opportunities/phd-vacancies-university-of-southampton-united-kingdom-robotic-monitoring-for-place-recognition-and-change-detection-in-dynamic-underwater-environments-c1cb18e8-c472-46e8-9a50-54c02cf5de44
Further details: Job Description and Person Specification £43,994 to £47,279 per annum, subject to bi-annual review due to exchange rate