We are looking for a motivated Master’s student interested in semiconductor memory technology, reliability engineering, and data analysis. The project will investigate activation energy in embedded RRAM devices and develop a practical model for predicting retention lifetime.
Candidate profile:
- Pursuing an MSc in Electrical Engineering, Applied Physics, Nanotechnology, Materials Science, Semiconductor Engineering, or a related discipline
- Strong analytical skills and an interest in semiconductor device physics and reliability
- Familiarity with statistical data analysis and scientific modeling
- Experience with Python, MATLAB, or similar data-analysis tools
- Ability to conduct an independent literature review and communicate technical findings clearly
- Curious, structured, and comfortable working with experts in a multidisciplinary environment