大型语言模型中的记忆风险缓解博士研究员
Mitigating memorisation risks in Large Language Models
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 • choose the relevant PhD Electronic & Electrical Engineering (7092) • add name of the supervisor in section 2 Applications should include: • a personal statement • your CV (resumé) • 2 academic references • degree transcripts to date
- 最近申请截止
- 2027-12-31
- 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
- • a personal statement
- • your CV (resumé)
- • 2 academic references
- • degree transcripts to date
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
- 该博士项目旨在开发隐私技术以检测、控制和消除大型语言模型（LLM）及多智能体AI系统中的训练数据记忆风险，具体方向包括审计记忆、缓解记忆（机器学习遗忘和隐私保护训练）以及多智能体系统中的数据与知识产权流向追踪。
- 申请条件
- 申请人必须拥有英国 2:1 荣誉学士学位或国际同等学历，专业背景为计算机科学、人工智能或相关学科，具备机器学习和 Python 编程的强力经验者优先。
- 待遇
- 提供针对英国及国际学生的多种竞争性资助机会，包括总统奖学金（Presidential Bursaries）、学院提供的竞争性奖学金（涵盖英国本土学费及生活费津贴），以及 Horizon Europe 学费减免（适用于符合条件的海外生）。
- 申请方式
- 通过南安普顿大学申请系统提交，需选择研究型项目（Research）、2027/28学年、工程与物理科学学院、全职或兼职、相关博士项目（Electronic & Electrical Engineering, 7092），并在第二部分添加导师姓名。
- 材料清单
- 个人陈述（personal statement）
- 简历（CV/resumé）
- 2封学术推荐信（academic references）
- 截至目前的学位成绩单（degree transcripts to date）
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
- 2027-12-31
- 学科
- 计算机科学
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Han Wu
- 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）
- 判定为博士研究项目主题
This PhD project develops privacy technologies to detect, control and remove such memorisation
- 语言与国际学生要求
We offer a range of funding opportunities for both UK and international students.
原文
View all current projects
Postgraduate research project
Mitigating memorisation risks in Large Language Models
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 Dec 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
Large Language Models memorise their training data and can reproduce personal information, copyrighted content and proprietary intellectual property. This PhD project develops privacy technologies to detect, control and remove such memorisation, from individual models to multi-agent AI systems, helping to build AI that respects both privacy and creators' rights.
Large Language Models (LLMs) and the AI agents built on them are transforming how we search, write and code. Yet their power comes with a risk: they memorise their training data and can reproduce personal data, copyrighted content or proprietary intellectual property (IP). These issues are central to data protection law and ongoing copyright disputes over AI.
This project takes a privacy-centred view of memorisation, using privacy technologies to detect, control and remove unauthorised information in LLMs.
Possible directions include:
• auditing memorisation: privacy attacks that reveal whether a model has memorised, or was trained on, specific personal or copyrighted data
• mitigating memorisation: machine unlearning and privacy-preserving training that remove or limit unwanted data influence with verifiable guarantees
• multi-agent systems: tracing how data and IP flow across the AI supply chain of models, datasets, tools and agents, drawing on ideas such as AI bills of materials to make these systems transparent and accountable.
The intended outcome is practical methods for auditing and safeguarding LLMs, supporting trustworthy AI that complies with data protection and copyright law.
You will join the cyberPUNK Lab led by Dr Han Wu in the Cyber Security group, working with an interdisciplinary team spanning law, finance, human-computer interaction and industry experts in AI governance. The exact focus can be shaped around your interests.
The School of Electronics & 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 Han Wu
Lecturer in Cyber Security
Research interests
• AI Privacy and Security
• Adversarial Machine Learning
• Distributed Machine Learning
Entry requirements
You must have a UK 2:1 honours degree or its international equivalent, in one of the following:
• computer science
• Artificial Intelligence
• or related disciplines
Strong experience in machine learning and Python programming 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
• choose the relevant PhD Electronic & Electrical Engineering (7092)
• add name of the supervisor in section 2
Applications should include:
• a personal statement
• your CV (resumé)
• 2 academic references
• degree transcripts to date
Contact us
Faculty of Engineering and Physical Sciences
If you have a general question, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Han Wu (h.wu@soton.ac.uk).