物理人工智能领域的超表面技术：用于消费电子产品的机器学习驱动纳米光子学

该项目致力于开发用于物理人工智能的下一代超表面技术，通过利用纳米结构光学硬件实现感测与信息处理。它结合先进的纳米制造技术与机器学习方法，以打造光学传感器与处理器，旨在提升在机器人技术和消费电子领域的性能。建议申请者具备光学、机器学习及纳米技术方面的背景知识。

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.

入学要求 您必须拥有英国2:1荣誉学位或其同等国际学位。

资助：竞争性资助 学费与资助 我们为英国本土学生和国际学生提供多种资助机会。符合条件的学生可通过“地平线欧洲”学费减免，自动免除国际学生学费与英国本土学生学费之间的差额。 大学通过竞争性遴选授予的校长助学金，为遴选排名靠前的申请人支付国际学生学费与英国本土学生学费之间的差额。 本校各学院通过竞争性遴选提供的博士奖助金，通常为遴选排名靠前的申请人支付按英国本土学生标准收取的学费，并提供生活津贴。 资助采用滚动授予方式，因此请尽早申请，以尽可能增加进入资助评选的机会。 如需更多信息，请访问我们的研究型研究生资助页面。

申请方式 您需： 选择课程类型（研究型）、2027/28学年、工程与物理科学学院 选择全日制或非全日制 搜索电子与电气工程博士项目（7092） 在申请表第2部分填写导师姓名 申请材料应包括： 研究计划书 您的CV（个人简历） 2份学术推荐信 截至目前的学位课程成绩单和证书 英语语言资格证明（如适用）