贝叶斯高维结构数据建模博士生
PhD Studentship: Bayesian Modeling of High-dimensional Structural Data
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
- 开发全面性的贝叶斯学习框架，用于高维结构数据的建模。
- 申请条件
- 至少 2.1 荣誉学位或硕士学位（或国际同等学历）在相关科学或工程学科。
- 待遇
- 每年 £21,805 的税前津贴和学费将被支付。
- 申请方式
- 请联系 Dr Nilabja Guha - nilabja.guha@manchester.ac.uk，提供当前学习水平、学术背景、相关经验和研究动机。
- 材料清单
- 当前学习水平
- 学术背景
- 相关经验
- 研究动机
由 @cf/meta/llama-3.3-70b-instruct-fp8-fast 生成，博士岗判定置信度 90%。
结构化信息
- 截止
- （Europe/London） 剩 20 天
- 学科
- 其他
- 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 Nilabja Guha
- 来源
- jobs.ac.uk（英国博士项目及学术招聘） · 最近核对 2026-10-07
判定依据（原文摘录）
- is_phd
This 3.5-year PhD project
- english_ok
Application deadline: All year round
- bachelor_ok
at least a 2.1 honours degree or a master’s
原文
Application deadline: All year round
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026.
We recommend that you apply early as the advert may be removed before the deadline.
In many applications such as biological sciences, social science, and engineering, we encounter high-dimensional observations. Bayesian approach can provide a flexible modeling framework for underlying structures in high dimension such as underlying covariance structure, conditional dependency graphs etc. With the change in data-generating mechanism, these high-dimensional structures may change with time, where the change can depend on latent factors or variables.
These projects will focus on developing a comprehensive Bayesian learning framework for this broad class of problems while focusing on specific applications. The goal would be to develop computationally efficient and scalable Bayesian learning methodologies with practical applications and establish relevant theoretical properties.
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.
To apply, please contact Dr Nilabja Guha - nilabja.guha@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project. £21,805 annual tax-free stipend set at the UKRI rate and tuition fees will be paid