面向物理AI的超表面技术：用于消费电子的机器学习赋能纳米光子学博士研究员
Metasurface technologies for physical AI: machine learning-enabled nanophotonics for consumer electronics
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 Electronic & Electrical Engineering (7092) • add name of the supervisor in section 2 of the application Applications should include: • research proposal • 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
- • research proposal
- • 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
- 本项目将开发用于物理AI的下一代超表面技术，利用纳米结构光学硬件将传感和信息处理更靠近物理世界。研究内容包括调查机器学习辅助的超表面设计方法、优化光学功能与下游AI任务（如特征提取），并在南安普顿大学先进的纳米加工设施上制造器件，同时提供逆向设计、纳米加工、光学表征及机器学习等跨学科培训，并有机会进行国际合作与交流。
- 申请条件
- 申请人必须拥有英国 2:1 荣誉学士学位或其国际同等学历。
- 待遇
- 提供针对英国及国际学生的多种资助机会（竞争性资助项目），包括地平线欧洲学费减免、校长奖学金以及涵盖学费和生活津贴的学院奖学金（具体依排名和资格而定）。
- 申请方式
- 通过南安普顿大学系统在线申请，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、PhD Electronic & Electrical Engineering (7092) 课程，并在申请表的第二部分添加导师姓名。
- 材料清单
- 研究计划 (research proposal)
- 简历 (CV)
- 2封学术推荐信 (academic references)
- 迄今为止的学位成绩单与证书 (degree transcripts and certificates to date)
- 英语语言资格证明（如适用）(English language qualification)
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
- 物理与天文
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Xu Fang
- 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）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
English language qualification (if applicable)
- bachelor_ok
You must have a UK 2:1 honours degree or its international equivalent.
原文
View all current projects
Postgraduate research project
Metasurface technologies for physical AI: machine learning-enabled nanophotonics for consumer electronics
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 will develop next-generation metasurface technologies for Physical AI, using nanostructured optical hardware to integrate sensing and information processing closer to the physical world. Building on recent EPSRC, Royal Society, and Leverhulme Trust funding, the project combines advanced nanofabrication, machine-learning-enabled optical design, and international collaboration.
Metasurfaces are planar nanostructures capable of manipulating the amplitude, phase, and polarisation of light, enabling unconventional functionalities in ultra-compact optical systems. In parallel, Physical AI is an emerging technological direction in which intelligent systems interact directly with the physical world through integrated sensing, computation, and actuation.
This project will bring these two areas together by developing metasurface-based optical sensors and processors. By extracting task-relevant information before digital processing, such systems could reduce latency and computational overhead. Potential applications include robotics, autonomous sensing, consumer electronics, and compact imaging systems.
You'll investigate machine-learning-assisted design approaches for metasurfaces, enabling the joint optimisation of optical functionality and downstream AI tasks such as feature extraction. Devices will be fabricated using the University of Southampton’s advanced nanofabrication facilities, with particular emphasis on scalable fabrication approaches that support future translation and commercialisation.
The project provides interdisciplinary training in:
• inverse design
• nanofabrication
• optical characterisation
• machine learning for physical and optical systems
The project will involve collaboration with leading international partners, including the Massachusetts Institute of Technology (MIT), Tokyo University of Agriculture and Technology, Nanyang Technological University, and several industrial partners. Opportunities may also arise for extended international research visits during the later stages of your PhD.
The School of Electronics and Computer Science 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 Xu Fang
Lecturer
Research interests
• Metasurfaces for automotive sensing and healthcare
• Extreme light manipulation at the nanoscale
Supervisors
Dr Eric Plum
Principal Research Fellow
Entry requirements
You must have a UK 2:1 honours degree or its international equivalent.
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 Electronic & Electrical Engineering (7092)
• add name of the supervisor in section 2 of the application
Applications should include:
• research proposal
• 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 Xu Fang (X.Fang@soton.ac.uk).