资深外延科学家

岗位职责:
1.负责MOCVD外延设备和工艺的日常运行
2.通过各种表征手段分析优化GaN材料质量
3.分析并且解决外延材料生长和MOCVD设备相关的技术问题
4.开发下一代GaN基高效蓝光/绿光(mini/micro)LED外延结构，如更短的生长时间，波长均匀性，良率，ESD，亮度等等，并导入量产
5.负责研发项目从立项到导入量产的整个过程，组建项目技术团队，负责项目团队的管理。

任职要求:
1.物理学、材料科学、电子工程、化学工程等相关学科的硕士或博士以上学历，具备5年以上的氮化物半导体器件方面，尤其GaN LED领域的实际工作经验
2.具备5年以上量产型MOCVD机台和技术开发的经验，尤其是GaN外延材料生长的经验 
3.非常熟悉了解三五族半导体材料的表征分析，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，并通过DOE，SPC以及相应的数据分析处理方法来分析root-cause并解决问题
5.熟练使用各种数据分析方法，以及掌握数据分析软件的使用，如JMP, MiniTab等
6.自律并可独立开展技术研究和开发的研究者，并具备优秀的团队沟通协调能力
7.可以适应短时间，高强度压力下的技术难题和事项的挑战，并且在专业范围以内或以外，通过有效的团队协作解决各种不同的问题
8.优先考虑美国和欧洲留学背景的应聘者；此外优先考虑中科院，北京大学，苏州纳米所，中国科学技术大学，吉林大学，南京大学，武汉大学，浙江大学，厦门大学，大连理工大学，山东大学等一本院校
9.专业的英语听、说、读、写能力
10.特别有潜力和优秀的面试者可适当放宽条件
 
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.