After obtaining a joint MSc in Micro and Nanotechnologies from EPFL, Grenoble INP and PoliTo, Amalia worked for several years in the microelectronics industry, combining data science and domain expertise. As a data scientist, she worked on projects such as anomaly detection for quality improvement and machine learning based test optimization, while in her previous work as an application engineer she often employed statistics and data analysis in order to address customers' challenges. During that time she discovered her passion for data and for working with customers, co-authored two patents and completed a COS in Data Science - Machine Learning from EPFL. Amalia joined the SDSC's industry collaborations cell in October 2019.
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