資深外延科學家

崗位職責:
1.負責MOCVD外延設備和工藝的日常運行
2.通過各種表征手段分析優化GaN材料質量
3.分析并且解決外延材料生長和MOCVD設備相關的技術問題
4.開發下一代GaN基高效藍光/綠光(mini/micro)LED外延結構，如更短的生長時間，波長均勻性，良率，ESD，亮度等等，并導入量產
5.負責研發項目從立項到導入量產的整個過程，組建項目技術團隊，負責項目團隊的管理。

任職要求:
1.物理學、材料科學、電子工程、化學工程等相關學科的碩士或博士以上學歷，具備5年以上的氮化物半導體器件方面，尤其GaN LED領域的實際工作經驗
2.具備5年以上量產型MOCVD機臺和技術開發的經驗，尤其是GaN外延材料生長的經驗 
3.非常熟悉了解三五族半導體材料的表征分析，如以下分析手段：High resolution x-ray diffraction (XRD), Photoluminescence (PL), Electroluminescence (EL), Atomic force microscopy (AFM), Ellipsometry, SIMS, etc
4.非常熟悉了解，并通過DOE，SPC以及相應的數據分析處理方法來分析root-cause并解決問題
5.熟練使用各種數據分析方法，以及掌握數據分析軟件的使用，如JMP, MiniTab等
6.自律并可獨立開展技術研究和開發的研究者，并具備優秀的團隊溝通協調能力
7.可以適應短時間，高強度壓力下的技術難題和事項的挑戰，并且在專業范圍以內或以外，通過有效的團隊協作解決各種不同的問題
8.優先考慮美國和歐洲留學背景的應聘者；此外優先考慮中科院，北京大學，蘇州納米所，中國科學技術大學，吉林大學，南京大學，武漢大學，浙江大學，廈門大學，大連理工大學，山東大學等一本院校
9.專業的英語聽、說、讀、寫能力
10.特別有潛力和優秀的面試者可適當放寬條件
 
Responsibility:
1. Responsible for the general operation of MOCVD systems.
2. Evaluate epitaxial material using the various characterization tools.
3. Troubleshoot and resolve materials and MOCVD equipment related issues.
4. Develop next-generation GaN-based Blue/Green (mini/micro) LED Epi processes with shorter process time, high uniformity, high yield, high ESD robustness, high LOP and etc.
5. Oversee entire R&D project progress; assemble and manage project team.

Qualifications:
1. Ph.D. (with 5+ years of applicable hands-on experience) in Physics, Chemical Engineering, Material Science, Electrical Engineering, or other related discipline(s). Master degree with strong background will also be considered.
2. 5 (5+) years of direct experience with commercial MOCVD process and equipment technology. Prior track record of GaN epitaxial material growth is a plus.
3.Prior experience in III-V materials characterization techniques such as: High resolution x-ray diffraction (XRD), Photoluminescence (PL), Electroluminescence (EL), Atomic force microscopy (AFM), Ellipsometry, SIMS, etc. is strongly desired.
4. Experience in semiconductor manufacturing epitaxy utilizing design of experiment (DOE), statistical process control (SPC), and methodical data analysis for process performance improvement and structured (root-cause) troubleshooting is essential.
5. Demonstrated proficiency in the use of statistical analysis programs for gathering and analyzing process data related to performance specifications, such as JMP, MiniTab.
6. A highly-motivated self-starter with ability to work independently and a strong team player with good communication skills.
7. Ability to adapt to changing priorities, thriving on technical challenges within and outside of core area of expertise, and to interact effectively across multi-functional teams.