高风险环境决策支持的人本人工智能(AI)博士研究员
Human-centred artificial intelligence (AI) for decision support in high-stakes environments
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 Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-09-30
- 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
- • 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
- 本项目探讨人工智能（AI）如何在保持人类判断力的同时，增强复杂、高风险环境下的决策能力。研究利用人因工程、认知心理学和人机交互的理论与方法，考察信任、透明度、工作负荷和问责制，以设计更安全、可解释、以人为本的AI系统。
- 申请条件
- 申请人需持有英国2:1荣誉学士学位（或国际同等学历），专业背景为人因工程、心理学，或具备复杂系统相关经验；必须理解定量研究方法及实验设计的使用；理解并具备机器学习或大语言模型能力者为佳。
- 待遇
- 提供竞争性资助机会（如学校的总统奖学金或院系奖学金），面向英国本土及国际学生，通常为优秀申请者涵盖英国水平的学费及生活成本津贴；资助按滚动方式发放。
- 申请方式
- 申请人需在线申请，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 Engineering & the Environment (7175)项目，并在申请第二部分添加导师姓名。
- 材料清单
- 简历（CV）
- 2封学术推荐信
- 迄今为止的学位成绩单与证书
- 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
- 2027-09-30
- 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 Anna-Stiina Wallinheimo, Dr Ben Waterson
- 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）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
English language qualification (if applicable)
- bachelor_ok
A UK 2:1 honours degree, or its international equivalent
原文
View all current projects
Postgraduate research project
Human-centred artificial intelligence (AI) for decision support in high-stakes environments
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 Sep 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 explores how artificial intelligence (AI) can enhance decision-making in complex, high-stakes settings while preserving human judgement. Drawing on human factors, cognitive psychology, and human-computer interaction, the research examines trust, transparency, workload, and accountability to inform safer, more explainable, human-centred AI systems.
Across domains such as transport, healthcare, emergency management, defence, and critical infrastructure, human operators often face an overwhelming volume of information and must make rapid, accurate decisions under uncertainty, time pressure, and high cognitive demand, where decision errors can have significant operational, societal, or life-threatening consequences.
While advances in AI, including machine learning and large language models, offer new opportunities to support human decision-making, effectively integrating AI into such complex, high-stakes decision-making environments while preserving human judgement remains a major challenge. This interdisciplinary project will focus on the human aspects of this challenge, investigating how AI system design can best foster collaboration that supports, rather than replaces, the human decision-maker.
Drawing on theories and methods from human factors, cognitive psychology, and human-computer interaction (HCI), the research will investigate the cognitive mechanisms underpinning human-AI collaboration. Research questions are likely to include how AI explanations influence trust and reliance, how system transparency affects operator understanding, and how AI support impacts cognitive workload, situation awareness, decision confidence, and accountability for the human decision-maker.
Ultimately, the aim is to develop evidence-based principles to inform the design of trustworthy and explainable AI systems that enhance human decision-making. The outcomes will support the safe, ethical deployment of AI technologies in high-stakes settings, ensuring intelligent systems remain aligned with human needs, capabilities, and values.
The School of Engineering 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 Anna-Stiina Wallinheimo
Research Fellow
Research interests
• Distributed Cognition
• Human-AI Interaction
• Human-Centred AI
Supervisors
Dr Ben Waterson
Professor
Research interests
• Road transport
• Artificial Intelligence
• Traveller Behaviour
Entry requirements
A UK 2:1 honours degree, or its international equivalent, in one of the following:
• Human Factors
• Psychology
or experience in complex systems.
An understanding of quantitative research methods and the use of experimental designs is essential.
An understanding of and capability in machine learning or large language models is also 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
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• 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 Anna-Stiina Wallinheimo (A-S.Wallinheimo@soton.ac.uk).