基于抗辐射忆阻器的空间自主智能储层计算博士研究员
Radiation-resilient memristor-based reservoir computing for autonomous space intelligence
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 Electronic & Electrical Engineering (7092) • 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
- 2027-12-31
- 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. 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
- 本项目将开发兼具超低功耗与固有抗辐射特性的基于忆阻器的储层计算硬件，通过研究空间辐射对忆阻器动力学的影响并设计自适应缓解策略，为未来卫星、行星探测和自主太空任务提供紧凑、节能的机载智能。
- 申请条件
- 申请人需要持有英国 2:1 荣誉学士学位或其国际同等学历。
- 待遇
- 学校提供多种针对英国和国际学生的资助机会，包括竞争性的总统奖学金和学院提供的奖学金（通常涵盖英国水平的学费和生活费津贴），具体取决于顶尖申请者的排名。
- 申请方式
- 申请人需通过学校系统申请，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 Electronic & Electrical Engineering (7092)项目，并在申请的第二部分添加导师姓名。
- 材料清单
- 简历（CV）
- 2封学术推荐信
- 至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
- 2027-12-31
- 学科
- 工程
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Firman Simanjuntak
- 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
- is_phd
This PhD project will investigate memristor-based reservoir computing
- bachelor_ok
A UK 2:1 honours degree, or its international equivalent.
原文
View all current projects
Postgraduate research project
Radiation-resilient memristor-based reservoir computing for autonomous space intelligence
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
Can a computer survive and learn in space? This project will develop memristor-based reservoir computing hardware that combines ultra-low power consumption with inherent radiation resilience. By investigating how space radiation affects memristor dynamics and designing adaptive mitigation strategies, the research will enable compact, energy-efficient onboard intelligence for future satellites, planetary exploration, and autonomous space missions.
Space missions increasingly require onboard intelligence to analyse sensor data, detect anomalies, and support autonomous operation while operating under severe constraints in power, mass, and radiation exposure. Conventional AI hardware can be energy intensive and vulnerable to radiation effects, creating a need for new computing technologies that are both efficient and resilient.
This PhD project will investigate memristor-based reservoir computing, a neuromorphic computing approach that exploits the intrinsic temporal dynamics of emerging electronic devices to process time-dependent data with minimal training overhead. The research will address a key challenge for future space systems: understanding how radiation affects memristor reservoir behaviour and developing strategies to maintain reliable computation in harsh environments.
The student will fabricate and characterise oxide-based memristors, evaluate their reservoir computing properties, and study their response to space-relevant radiation conditions, including total ionising dose and displacement damage. Experimental devices will be integrated with FPGA-based platforms to develop low-power hardware demonstrators for applications such as spacecraft health monitoring, telemetry anomaly detection, and onboard sensor-data processing.
Expected outcomes include new understanding of radiation effects on neuromorphic hardware, physics-informed models linking device degradation to computational performance, and adaptive mitigation techniques for radiation-resilient edge AI. The project combines materials science, nanoelectronics, neuromorphic computing, machine learning, and space engineering.
The student will benefit from access to world-class cleanroom fabrication facilities, advanced device characterisation equipment, HPC resources, FPGA development platforms, and international collaborations in neuromorphic computing and space technologies. The project offers opportunities for conference presentations, high-impact publications, and engagement with industrial and aerospace partners.
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 Firman Simanjuntak
MIET, MInstP, SMIEEE, FHEA
Lecturer
Research interests
• Data storage, AI-hardware accelerator, secured hardware and sensors
• Nanoelectronics for space and nuclear environments
Entry requirements
A UK 2:1 honours degree, or its international equivalent.
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.
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 Electronic & Electrical Engineering (7092)
• 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
If you have a general question, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Firman Simanjuntak (f.m.simanjuntak@soton.ac.uk).