EMPA
Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain.
The Coating Technologies Group in Empa's Laboratory for Surface Science & Coating Technologies develops next-generation functional thin-films through innovative deposition processes and high-throughput materials screening
Postdoc Researcher in Accelerated Thin Film Development & Materials Informatics
Conduct combinatorial physical vapor deposition and automated characterization together with other team membersPerform accelerated optical degradation tests of transparent conductive materialsApply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film developmentYour work will be part of a larger effort in our laboratory to develop tools and methods to accelerate the development of new functional thin films. In addition to the work described above, you will have the chance to contribute to many other exciting projects ranging from autonomous sputter deposition to the development of new ferroelectric materials for non-volatile memory applications. Your profile
- PhD degree in physics, materials science, chemistry, electrical engineering or a related discipline
- Strong background in materials informatics and data science
- Proficiency in Python programming
- Experience in machine learning for materials development (e.g. supervised and active learning, feature engineering)
- Interest in lab automation (LabView experience is a plus)
- Knowledge of UHV and thin-film deposition is advantageous
- Excellent communication skills in English
- Strong academic track-record and publication history