电池界面量子与AI驱动原子模拟预测模型博士研究员
Advancing predictive models for battery interfaces through quantum and AI-driven atomistic simulations
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 Chemistry (7189) • 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
- 2027-03-31
- 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
- • 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
- 本项目旨在通过开发电池界面的预测模型来塑造能源储存的未来，结合大规模量子模拟与AI驱动的力场，揭示固体电解质界面膜（SEI）在运行条件下的形成、反应和降解机制，并通过与法拉第机构多尺度建模项目的合作支持下一代电池的发展。
- 申请条件
- 申请人必须持有英国2:1荣誉学位或其国际同等学历，专业背景为化学、物理或材料科学；具备密度泛函理论（DFT）计算或其他原子模拟方法经验者优先。
- 待遇
- 提供竞争性资助机会（如总统奖学金或学校提供的奖学金），通常涵盖英国本土学费及生活费津贴；欧洲地平线费减免可自动补足合格学生的海外学费与英国学费差额。资助按滚动方式发放。
- 申请方式
- 申请人需通过南安普顿大学系统在线申请，选择研究型项目、2027/28学年、工程与物理科学学院、全职或兼职，搜索“PhD Chemistry (7189)”项目，并在申请表的第二部分添加导师姓名。
- 材料清单
- 个人简历 (CV)
- 2封学术推荐信
- 截至目前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
- 2027-03-31
- 学科
- 能源
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Chris Skylaris
- 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
Advancing predictive models for battery interfaces through quantum and AI-driven atomistic simulations
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 Mar 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
Help shape the future of energy storage by developing predictive models of battery interfaces. This PhD combines large-scale quantum simulations with AI-driven force fields to reveal how the solid electrolyte interphase forms, reacts and degrades under operating conditions, supporting next-generation batteries through collaboration with the Faraday Institution’s Multiscale Modelling project.
Help shape the future of energy storage by developing predictive models of one of the most important regions in a battery: the solid electrolyte interphase (SEI). The SEI is critical to battery performance and lifetime, yet its formation, chemical reactions, degradation and behaviour under operating conditions remain challenging to predict.
This PhD will combine large-scale quantum simulations using ONETEP (Order-N Electronic Total Energy Package) with reactive AI-driven force fields to create high-fidelity atomistic models of battery interfaces. You will help develop models that incorporate long-range electrostatics and applied-potential effects, enabling predictive simulations of SEI formation and evolution. The research may also explore chemical reactions, coatings, additives and defects within SEI layers.
The intended outcome is a hierarchy of transferable predictive models that can deepen understanding of interfacial electrochemistry and support the development of next-generation batteries. These approaches could ultimately be adapted to other battery chemistries, including sodium-ion systems, and to other interfaces such as the cathode electrolyte interphase.
The project is aligned with the Faraday Institution’s Multiscale Modelling (MSM) project, providing opportunities to interact with researchers across a multi-institution consortium and participate in its activities. You will gain cutting-edge computational experience at the intersection of computational chemistry, atomistic modelling, quantum simulation, AI-driven force fields, electrochemistry and energy-storage science.
The School of Chemistry and Chemical 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
Professor Chris Skylaris
Professor of Computational Chemistry
Research interests
• Development of large-scale electronic structure methods, based on Density Functional Theory within the ONETEP program (onetep.org)
• Development of atomistic and multiscale simulation methods for materials using quantum and classical methods, and machine-learned potentials
• Application of these simulation methods to discover advanced materials in technologically relevant problems such as batteries, hydrogen fuel cells and drud optimisation
Entry requirements
You must have a UK 2:1 honours degree or its international equivalent, in one of the following:
• chemistry
• physics
• materials science
Experience with DFT calculations or other atomistic simulation methods 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
• search for programme PhD Chemistry (7189)
• 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 Professor Chris Skylaris (C.Skylaris@soton.ac.uk).