具身智能体中涌现的多模态通信博士研究员
Learning to communicate and collaborate: emergent multimodal communication in embodied agents
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
- 2027-06-30
- 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
- 本项目研究具身智能体和机器人在没有预先设计语言的情况下，如何通过视觉、声音、触觉和手势等可用模态学习相互沟通和协作，并探讨异构实体间的协议互操作、模态选择、意图传达以及适应性策略。
- 申请条件
- 申请者必须持有英国 2:1 荣誉学位或同等国际学历（计算机科学、机器人学、工程学、数学、物理学、认知科学或相关领域），具备良好的编程技能（Python 和深度学习框架），具有强化学习、机器人学或仿真环境、多智能体系统或人机交互经验者为佳。
- 待遇
- 提供针对英国及国际学生的竞争性资助机会（如总统奖学金、学校提供的学费及生活费资助等），具体视评选情况而定。
- 申请方式
- 通过南安普顿大学官网进行在线申请，选择研究型项目（Research）、2027/28学年、工程与物理科学学院，搜索“PhD Computer Science (7089)”，并在申请的第二部分填写导师姓名。
- 材料清单
- 研究计划书
- 简历
- 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
- 2027-06-30
- 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
- Daniela Mihai
- 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
Learning to communicate and collaborate: emergent multimodal communication in embodied agents
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
30 Jun 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
Robots and embodied agents that collaborate need ways to share what they perceive, intend and need. This PhD investigates how embodied agents learn to communicate through the modalities available to them, such as vision, sound, touch, and gesture, to collaborate effectively with one another and people, without a pre-designed language.
Most research on emergent communication takes place in abstract, disembodied settings using discrete tokens. Real collaborative systems, such as robot teams, human–robot teams and autonomous vehicles, act in physical or simulated space with different sensors, bodies and constraints, and cannot assume a pre-shared language. Recent work shows that agents with different perceptual modalities invent different, grounded protocols, raising the question of how heterogeneous embodied agents learn to coordinate.
Communication in these settings is shaped by what each agent can sense, do and afford to transmit, so effective protocols must be grounded in the body and the task rather than imposed from outside. Understanding how they arise is a prerequisite for deploying collaborative robots that people can understand and trust.
This project will study how embodied agents develop communication through interaction in collaborative tasks, in simulation and potentially on physical robots. Possible directions include:
• how protocols interoperate across heterogeneous entities and sensors
• how agents choose a modality (visual, auditory, gestural, spatial) to suit the task, partner and environment
• how teams communicate plans, intentions and spatial information
• how communication strategies adapt when partners, tasks or conditions change
• how emergent communication can be made transparent and interpretable to human collaborators
You will shape the project towards your strengths, whether in multi-agent reinforcement learning, robot learning, human–robot interaction or the theory of language emergence. The project benefits from links with the University's robotics community and interdisciplinary connections in cognitive science and linguistics, and contributes to the trustworthy deployment of collaborative AI and robotic systems.
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
DM
Dr Daniela Mihai
New Frontiers Fellow
Supervisors
Professor Jonathon Hare
BEng (Hons), PhD, FHEA, SMIEEE
Professor
Research interests
• My main research interests lie in the area of representation learning;
• The long-term goal of my research is to innovate techniques that can allow machines to learn from and understand the information conveyed by data and use that information to fulfil the information needs of humans.
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent, in one of the following:
• computer science
• robotics
• engineering
• mathematics
• physics
• cognitive science
• a related field
Essential skills:
• good programming skills (Python and Deep Learning frameworks)
Desiderable skills:
• experience with reinforcement learning, robotics or simulation environments, multi-agent systems or human–robot interaction
We particularly welcome applicants with interdisciplinary backgrounds.
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 Daniela Mihai (A-D.Mihai@soton.ac.uk).