用于光子与量子材料建模的量子库存储计算

该项目致力于推动量子储库计算技术（QRC）的发展，以用于模拟和设计复杂的量子与光子系统。项目将涉及理论模型的构建及大规模数值模拟工作，重点强调量子动力学与机器学习任务之间的关联。申请者应具备数值建模与编程方面的经验。

About the project Quantum physics and artificial intelligence are converging to change how complex light-matter systems are modelled and designed. This project will develop quantum reservoir computing as a theoretical and computational framework that uses the intrinsic dynamics of quantum systems to enable efficient learning, prediction and inverse design of photonic and quantum materials. The research will advance quantum reservoir computing (QRC) as a computational paradigm for modelling and designing complex quantum and photonic systems. Rather than relying only on data-intensive or brute-force numerical approaches, QRC exploits coherence, memory and nonlinearity in quantum dynamics as resources for information processing and learning. You will develop rigorous theoretical models and large-scale numerical simulations that reveal how quantum dynamics can perform tasks analogous to neural networks. The work will connect open quantum systems, photonics, machine learning and high-performance computing, with an emphasis on physically interpretable methods and architectures. You will be based at the Optoelectronics Research Centre (ORC) , a world-leading photonics institute with extensive experimental and computational facilities. The project offers training in quantum theory, numerical simulation, machine learning and high-performance computing, with access to large CPU and GPU clusters. The research programme will focus on: establish physically interpretable QRC algorithms capable of capturing strongly correlated and open quantum systems explore quantum-neuromorphic architectures using computational models of superconducting, photonic and hybrid reservoirs, identifying routes to energy-efficient learning apply these frameworks to the inverse design of photonic and quantum structures, testing how QRC can accelerate discovery and optimisation in a fully computational setting The School of Optoelectronics (ORC) 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荣誉学位或其国际等效学位，且所学专业属于以下领域之一： 物理学 光子学 电气或电子工程 应用数学 计算机科学 一个密切相关的学科领域 必备技能： 通过本科、硕士或研究项目获得的数值建模与科学编程经验 理想的技能： 先前对量子力学、开放量子系统、光子学或机器学习的学习经历 拥有使用 Python、C++、Julia 或 MATLAB 的经验，或能够利用高性能计算环境

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。 如需了解更多信息，请访问我们的研究生研究资助页面。

如何申请 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 搜索博士项目 PhD ORC（7097） 在申请表第2部分填写导师姓名 申请材料应包括： 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）