控制与神经科学方向博士职位
Research Studentship in Control and Neuroscience: Model-based Prediction and Control of Seizure-like Events
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。
AI 中文速览
- 研究内容
- 本项目旨在开发用于预测活体神经网络中癫痫样事件的数据驱动模型，结合控制理论、机器学习和计算神经科学，并在小鼠脑片多电极记录上进行验证，随后探索闭环多电极阵列的基于模型的刺激协议实现。
- 申请条件
- 要求申请者在工程学、计算机科学、物理学或数学领域获得一等学位或强2:1学位，并具备优秀的英语书面和口头沟通能力。具备控制理论、机器学习、计算神经科学、编程或实时硬件经验者优先。
- 待遇
- 提供为期3.5年的D.Phil.奖学金，学费按英国学生标准全额覆盖（每年至少10,940英镑），生活津贴第一年及后续两年半每年至少约21,805英镑。
- 申请方式
- 申请人需提交研究生申请表，并在申请中注明引用代码 27ENGCO_TB。申请截止日期为2026年12月2日中午，入学时间为2027年10月。
- 材料清单
- graduate application form
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
结构化信息
- 截止
- （Europe/London） 剩 53 天
- 学科
- 神经科学
- 合同类型
- 雇佣合同
- 原文薪资
- GBP 21,805 / 年（税前）
- 税后月薪（估）
- ¥13,700；房租后 ¥5,400
- 估算假设
- 单身、无子女、雇佣合同的粗略估算，以学校 offer 为准；扣除率 18%；汇率日期 2026-10-01
- 原帖发布
- 本站收录
- 内容更新
- 导师
- Dr Thiago B. Burghi
- 来源
- jobs.ac.uk（英国博士项目及学术招聘） · 最近核对 2026-10-09
- 详情核验
判定依据（原文摘录）
- is_phd
3.5-year D.Phil. studentship
- english_ok
Excellent English written and spoken communication skills.
- bachelor_ok
A first class (or strong 2:1) degree in any of Engineering, Computer Science, Physics, Mathematics.
原文
3.5-year D.Phil. studentship
Supervisor: Dr Thiago B. Burghi
This project will develop data-driven models for predicting seizure-like events in living neural networks. Such events can be induced in brain slices and share many features with epileptic seizures in the human brain. The underlying challenge is to obtain predictive models of extracellular neural activity that remain interpretable from the mechanistic viewpoint of biological neuromodulation. The student will have the freedom to develop their own modelling approaches, drawing on ideas from control theory, machine learning and computational neuroscience. A promising starting point is provided by Recurrent Mechanistic Models (RMMs), which combine state-space systems and artificial neural networks to capture neural dynamics. Models will be developed and validated using high-density multielectrode recordings from mouse brain slices.
The project will then explore the implementation of model-based stimulation protocols using closed-loop multielectrode arrays. The studentship forms part of Dr Burghi’s Royal Society University Research Fellowship, “Data-driven closed-loop control of living neural rhythms” and will be based in Oxford’s Control Group. Research will be carried out in collaboration with Prof Ed Mann’s laboratory in the Department of Physiology, Anatomy and Genetics, with opportunities to work with developers of multielectrode technology. The student will develop expertise in system identification, machine learning and neuroengineering, contributing to fundamental research on epileptiform dynamics and the development of principled closed-loop neurostimulation.
Eligibility
This studentship is funded through the Department of Engineering Science at the University of Oxford and is open to home students (full award – home fees plus stipend).
There may be flexibility to support international students. If you are an international student and want to apply for this studentship, please contact the supervisor to see whether the flexibility might be available for you.
Award Value
Course fees are covered at the level set for UK students (at least £10,940 p.a.). The stipend (tax-free maintenance grant) is at least c. £21,805 p.a. for the first year, and at least this amount for a further two and a half years.
Candidate Requirements
Prospective candidates will be judged according to how well they meet the following criteria:
• A first class (or strong 2:1) degree in any of Engineering, Computer Science, Physics, Mathematics.
• Excellent English written and spoken communication skills.
Experience in one or more of the following areas is desirable:
• Control theory and/or system identification
• Machine learning and scientific computing
• Computational neuroscience and biophysical modelling
• Programming and software development
• Real-time hardware
Application Procedure
Informal enquiries are encouraged and should be addressed to Dr Thiago Burghi at control@eng.ox.ac.uk .
Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website .
Please quote 27ENGCO_TB in all correspondence and in your graduate application.
Application deadline: noon on 2 nd December 2026 (In line with the December admissions deadline, set by the University)
Start date: October 2027 £21,805 p.a.