循环硅和碳化硅博士职位

PhD position in circular silicon and silicon carbide for additive manufacturing

University of Twente · 荷兰 · Enschede

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
该项目旨在开发硅和碳化硅的循环生产路线,重点研究将硅富废料转化为高纯度粉末,并使用机器学习模型优化粉末特性和工艺参数
申请条件
原文未说明
待遇
EUR 3204 - 4051 per month
申请方式
原文未说明
材料清单
  • 原文未说明

由 @cf/meta/llama-3.3-70b-instruct-fp8-fast 生成,博士岗判定置信度 100%。

结构化信息

截止
(Europe/Amsterdam) 剩 15 天
学科
材料科学
合同类型
雇佣合同
原文薪资
EUR 3,204–4,051 / 月(税前)
税后月薪(估)
¥19,000–¥24,000;房租后 ¥11,100–¥16,100
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 25%;汇率日期 2026-10-01
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来源
AcademicTransfer(荷兰学术招聘) · 最近核对 2026-10-07
判定依据(原文摘录)
  • is_phd
    PhD position
  • english_ok
    international environment
原文

We offer a fully funded, four-year PhD position at the University of Twente focused on developing circular production routes for silicon and silicon carbide, key materials for high-temperature and high-performance applications. The project brings together materials science, powder technology, additive manufacturing, and data science.

Silicon carbide is widely used in demanding thermal, structural, and electronic applications, yet its production is energy-intensive and relies on global supply chains. At the same time, the photovoltaic and semiconductor industries generate large volumes of silicon-rich waste: up to 75% of silicon can be lost across the value chain, while recycling rates remain around 5%. Existing recycling routes largely downcycle this material into lower-value compounds and do not produce powders with the quality required for advanced manufacturing.

This PhD project aims to address that gap. You will develop and optimise routes for converting silicon-rich waste streams into high-purity powders. Using mechanochemical processing, you will investigate and control phase formation, particle size distribution, morphology, and flowability. You will then establish additive manufacturing process windows for these circular powders using both binder-free and binder-based additive manufacturing approaches, investigating melt behaviour, densification, defect formation, and microstructure in materials.

A distinctive element of the project is its data-driven approach. Together with colleagues at Saxion University of Applied Sciences, you will contribute to the development of machine-learning models that connect powder characteristics and process parameters with the properties of the final components. These models will support faster feedstock qualification and enable predictive quality control.

You will work in an interdisciplinary and international environment alongside academic researchers and industrial partners spanning the full value chain—from waste recovery and silicon processing to powder qualification, additive manufacturing, and advanced ceramics. The project offers strong opportunities to publish high-impact research while developing technologies with immediate industrial relevance and clear potential for sustainability impact.

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