法国CEA LETI MINATEC材料科学博士后职位
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Job description:
The development of advanced photovoltaic and power electronics applications share common challenging requirements for advanced and traceable metrology. The non-destructive characterization of electronic structure, 3D compositional, chemical structure and electrical properties are required to improve the performance and efficiency of energy thin film materials applications. In addition, appropriate methodologies must be developed in order to investigate the impact of stress factors such as operating temperature on advanced thin film materials properties that could affect the durability of the devices.
In this project, you will develop and improve advanced non-destructive characterization methods for material research and development for energy applications in order to allow for traceable measurement and characterization of physical, chemical and electrical properties of materials such as indium-free transparent conductive oxides and power electronic related materials. Analytical methodologies will be optimized: VUV-ellipsometry and UPS measurements to get access to electronic structures, improved Grazing-incidence X-ray fluoresence (GiXRF) measurements for reference-free chemical depth-profiling with trace level sensitivity. Different analytical methods (e.g. GIXRF, AR-XPS, X-ray reflectometry, broadband spectroscopic ellipsometry) will be compared to test the reliability of the methods and to obtain complementary characteristics of the investigated material systems in order to support the optimization procedures. The properties of the materials will be evaluated under stress conditions (temperature) which will increase the value of this work for end-users.
Experience requirements:
You have completed a PhD in Material Science. Besides having a relevant research experience in the characterization of inorganic materials with non-destructive methods, including X-ray, optical and if possible electrical techniques, you are familiar with the required programming skills to perform advanced data analysis (working knowledge of programming in Python and Matlab). The project is multidisciplinary and involves collaborations with other groups at the institute as well as a number of external collaborations. You should have a strong interest in a multidisciplinary, collaborative approach. Independent thinking, team spirit and communication are crucial for a successful development of the project. In addition, you must be advanced in English and, if possible, in French languages….
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