What You'll Do
You'll contribute to the development of anomaly detection systems for Residual Gas Analyzers (RGAs), critical instruments in semiconductor fabrication. Working remotely, you'll engage with real-world datasets and existing algorithmic models, gaining insight into how data science integrates with physical systems.
Through exploratory analysis and visualization, you'll uncover patterns in multivariate sensor data and assess the effectiveness of current detection methods. You'll prototype potential improvements, test their performance, and refine approaches based on results. Regular interaction with mentors will guide your progress as you prepare to present your findings to the team.
Requirements
We're looking for someone with a strong curiosity about the connections between mathematics, physics, engineering, and software development. While formal experience is not required, a foundational understanding of data analysis concepts and an eagerness to work with real technical datasets is essential. You should be comfortable learning within an established codebase and exploring complex, high-dimensional data.
Benefits
This role offers direct mentorship from professionals experienced in both data science and sensor engineering. You’ll complete a meaningful project using actual industrial data, giving you practical experience that bridges theory and application. The remote structure allows flexibility while maintaining close collaboration with the team.
