多模态大语言模型论证与证据理解博士研究员
Multimodal LLMs for argument and evidence understanding
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 Computer Science (7089) • 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
- 2027-07-01
- 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
- 本项目将探索多模态大语言模型（LLMs）如何跨文本、音频、图像和视频理解论证，开发利用LLMs、视觉语言模型（VLMs）、多模态推理和论证挖掘来识别主张、证据及关系的方法。
- 申请条件
- 申请人需持有计算机科学、人工智能、数据科学或紧密相关定量学科的英国2:1荣誉学士学位（或同等国际学历），具备扎实的Python编程实践经验，且由于经费限制，仅邀请英国和欧盟候选人申请。
- 待遇
- 竞争性学生资助通常为名列前茅的申请者涵盖英国水平的学费以及生活费津贴，资助按滚动方式发放。
- 申请方式
- 申请人需通过大学系统选择研究型项目（2027/28学年，工程与物理科学学院），选择全职或兼职，搜索PhD Computer Science（7089）项目，并在申请第二部分添加导师姓名。
- 材料清单
- 研究计划书
- 简历（CV）
- 2封学术推荐信
- 至今为止的学位成绩单和证书
- 英语语言资格证明（如适用）
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
- 2027-07-01
- 学科
- 计算机科学
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Dr Rafael Mestre, Professor Stuart Middleton
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-24
- 详情核验
判定依据（原文摘录）
- eligibility_labels
Due to funding limits, only UK and EU-based candidates are invited to apply.
原文
View all current projects
Postgraduate research project
Multimodal LLMs for argument and evidence understanding
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
1 Jul 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 explore how multimodal large language models (LLMs) can understand arguments across text, audio, images, and video. You'll develop methods using LLMs, vision-language models (VLMs), multimodal reasoning, and argument mining to identify claims, evidence, and relationships.
Multimodal LLMs can process text, speech, images, and video, but still struggle to understand how claims, evidence, and counterarguments connect across these different forms of communication. Addressing this problem requires models that can identify argumentative structures, integrate information across modalities, reason with this information and explain what evidence supports their conclusions.
In this project, you'll develop and evaluate new methods for multimodal argument understanding. Depending on your interests and experience, you could investigate:
• large language models and multimodal reasoning for identifying claims, premises, evidence, and argumentative relationships
• connecting spoken or written claims with visual evidence
• analysing arguments across long complex discussions
Possible methods include multimodal reasoning, multimodal CoT distillation, multimodal retrieval, structured prediction, retrieval-augmented generation, and combinations of neural and symbolic approaches.
You'll have flexibility to shape precise methods, modalities, and applications. Potential directions include:
• developing new datasets and evaluation methods
• improving cross-domain generalisation
• testing whether models use multimodal evidence faithfully
• designing more interpretable and reliable systems
Applications might include online discussion, political debate, public deliberation, or other forms of written, spoken, and visual communication.
The project offers the opportunity to contribute across natural language processing, multimodal machine learning, computer vision, and audio analysis. You'll develop a coherent technical contribution around your strengths while gaining experience of interdisciplinary research and the wider implications of AI for real-world communication.
You'll join the School of Electronics and Computer Science. You'll have access to professional-development opportunities that may include teaching experience, engagement with networks such as the Alan Turing Institute and Responsible AI UK programme, and support from Future Worlds to explore the commercial potential of your research.
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 Rafael Mestre
PhD, MSc, BSc
Lecturer
Research interests
• Emerging technologies
• Multimodal AI
• Applied and responsible AI
Supervisors
Professor Stuart Middleton
Professor of Natural Language Processing
Research interests
• Natural Language Processing: Large Language Models
• Human-in-the-loop LLMs: Rationale-based learning, Active learning, Adversarial defence, Adversarial training, Interactive sense making.
• Information Extraction: Text/Behaviour classification, Few/Zero shot learning, Location extraction, QA, RAG, Event extraction, Data Rescue, Argument mining.
Entry requirements
A UK 2:1 honours degree, or its international equivalent, in one of the following:
• computer science
• artificial intelligence
• data science
• a closely related quantitative discipline
Practical programming experience in Python is essential.
Applicants are strongly encouraged to have a first-author publication in peer-reviewed natural language processing, machine learning, or a closely related area.
Experience with machine learning or natural language processing through a dissertation, research project, employment, or substantial independent work is desirable.
Experience with deep learning, large language models, audio, computer vision, or multimodal data would be helpful but is not required. No previous background in argument mining is expected.
Due to funding limits, only UK and EU-based candidates are invited to apply.
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 Computer Science (7089)
• 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 Rafael Mestre (R.Mestre@soton.ac.uk).