拉夫堡大学PhD Position in Stochastic analysis and modelling of flow boiling申请条件要求-申请方
主办方
拉夫堡大学
PhD直招介绍
About the Project
Flow boiling is one of the most efficient heat transfer mechanisms and plays a critical role in modern energy systems, including electronics cooling, renewable energy, and advanced thermal management technologies. However, its practical deployment is often limited by the lack of reliable predictive models, due to the complex and inherently stochastic nature of multiphase flow phenomena.
This PhD project aims to develop next-generation, uncertainty-aware stochastic models for flow boiling, moving beyond traditional deterministic approaches. The research will combine advanced data-driven modelling with high-resolution experimental analysis. You will work with an established flow boiling facility equipped with state-of-the-art optical diagnostics to generate and analyse time-resolved experimental data, providing a unique opportunity to bridge fundamental science with real-world engineering applications.
The successful candidate will join a dynamic, industry-collaborative research team and will develop expertise at the interface of thermal sciences, data science, and machine learning.
Key Responsibilities：
Develop and implement automated image-processing algorithms to extract and quantify statistical characteristics of flow boiling processes
Develop stochastic flow boiling models and rigorously quantify associated uncertainties
Develop uncertainty-aware artificial neural network models for predictive modelling of multiphase heat transfer
94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Supervisors
Primary supervisor: Huayong Zhao
Secondary supervisors: Steven Kenny, Ed Long
拉夫堡大学 PhD Position in Stochastic analysis and modelling of flow boiling项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
Fees and funding
This PhD project is jointly funded by Loughborough University and Caterpillar, one of the University's long-standing industrial collaborators, providing the successful candidate with the opportunity to engage with both academic and industry partners throughout the project.
The studentship provides an enhanced tax-free stipend of £22,437 per year, for a minimum of 3 years, with future increases applied in line with any annual uplift to the UKRI base stipend rate.
The studentship is open to UK/International students and will cover the full tuition fees.
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申请要求
Entry requirements
Applicants should hold, or expect to achieve, a first-class or high upper second-class (2:1) honours degree (or equivalent) in Mechanical Engineering, Physics, or a closely related discipline. A relevant Master’s degree or prior research experience in experimental and/or analytical multiphase thermofluids systems would be advantageous but not essential.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website( https://www.lboro.ac.uk/study/apply/english-language-requirements/ ).
报名方式
招生人信息
Dr H Zhao, Dr E Long
Professor Email:
H.Zhao2@lboro.ac.uk
E.J.Long@lboro.ac.uk
Professor Detail:
https://www.lboro.ac.uk/schools/meme/staff/huayong-zhao/
https://www.lboro.ac.uk/schools/meme/staff/ed-long/
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