机械工程博士职位:聚变反应堆中三位氢的产生和热交换问题研究
PhD Studentship: Mechanical Engineering, Fusion, Digital: An AI Enhanced Modelling of Coupled Tritium Breeding and Heat Exchange for Fusion Breeder Blankets
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AI 中文速览
- 研究内容
- 该项目将研究聚变反应堆中三位氢的产生和热交换问题,重点关注中子传输和三位氢产生的优化
- 申请条件
- 原文未说明
- 待遇
- GBP 21805.00 per year
- 申请方式
- 原文未说明
- 材料清单
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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 5 天
- 学科
- 能源
- 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
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- 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
PhD Studentship
- english_ok
Applications may be submitted in Welsh and any application submitted in Welsh will be treated no less favourably than an application submitted in English
原文
In future fusion power plants operating with a closed-loop fuel cycle, breeding a sufficient quantity of tritium is essential for sustained power generation. A key performance metric is the Tritium Breeding Ratio (TBR), which depends on several tightly coupled factors, including breeder blanket design, plasma-facing surface area, neutron transport, material composition, and cooling performance. Since cooling is also intrinsically linked to heat extraction, structural integrity, and irradiation-induced material damage, TBR optimisation represents a highly coupled neutronic–thermomechanical challenge.
This PhD project will investigate this coupled problem within the context of UK-specific tokamak reactor designs, working collaboratively with other researchers and doctoral students across related areas. The primary focus will be on neutronics and optimisation of TBR within realistic fusion operating conditions.
Initially, the research will employ Monte Carlo neutronics methods using tools such as OpenMC (or equivalent) to model neutron transport and tritium breeding behaviour within breeder blanket configurations. The project will then extend toward accelerated predictive methodologies using machine learning and AI approaches, including surrogate modelling and large language model (LLM)-assisted information extraction from openly available international fusion datasets and literature.
Applications may be submitted in Welsh and any application submitted in Welsh will be treated no less favourably than an application submitted in English. Please refer to the University’s Welsh Language Policy on Awarding Grants.