Silicon Photonics Device Engineering Intern

GlobalFoundries inc.; Town of Malta (NY); Vor Ort; USD 28.000 - 55.000; Teilzeit

Benefits dieser Stelle

Accommodation available

Zusammenfassung

GlobalFoundries is seeking a Silicon Photonics Device Engineering Intern to assist in developing and qualifying silicon photonic devices for high-speed interconnect and sensing applications. You will analyze inline data and electrical/optical measurements to identify opportunities to improve performance, variability, and manufacturability.

The role focuses on data mining and statistical analysis across process, electrical, and optical datasets, with mentoring and professional development as part

Qualifikationen

• Education – At least a sophomore at time of application; pursuing a bachelor’s, master's, or PhD in Electrical Engineering, Computer Engineering, Materials Engineering, Photonics, Optics, Physics, or related field; minimum 3.0 GPA.

Aufgaben

• Analyze in-line process, electrical, and optical data for silicon photonic devices.
• Support evaluation of process or design improvements to reduce variability and improve performance.
• Assist with identifying measurements to predict device figures of merit and enable new tests.
• Perform data mining, correlation, and statistical analysis across datasets; document methods and results.

Kenntnisse

Strong written and verbal comms

Python or R scripting

Data analysis

Leadership experience

Ausbildung

Bachelor’s/Master’s/PhD in Electrical Engineering, Computer Engineering, Materials Engineering, Photonics, Optics or related field

Tools

Python

R

Statistical analysis tools

Jobbeschreibung

GlobalFoundries is seeking a Silicon Photonics Device Engineering Intern to assist in developing and qualifying silicon photonic devices for high-speed interconnect and sensing applications. You will analyze inline data and electrical/optical measurements to identify opportunities to improve performance, variability, and manufacturability.

The role focuses on data mining and statistical analysis across process, electrical, and optical datasets, with mentoring and professional development as part