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95103, San Jose, CA
GaN Characterization Intern

GaN Characterization Intern

Power Integrations

Posted 4 days ago, valid for 18 days

San Jose, CA 95103, US

$40 - $45 per hour

Full Time

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Sonic Summary

The GaN Characterization Intern position is located in San Jose and focuses on executing experiments related to GaN devices.
Interns will conduct static and dynamic characterization, TDDB-based lifetime studies, and perform data analysis and interpretation.
A key deliverable for the role is a concise report with comparison charts and tables for customer communications.
Candidates are expected to have hands-on experience with semiconductor power device characterization and be MS/PhD students in relevant fields.
The hourly pay for this internship ranges from $40 to $45, and candidates should have relevant experience to negotiate within this range.

Internship Title: GaN Characterization Intern

Location: San Jose

Role Description:

Internship Summary, Responsibilities, and Deliverables:

Intern would be responsible for executing experiments including

static/dynamic characterization of discrete or cascode GaN devices
TDDB-based lifetime study and
data analysis and interpretation

Deliverable would be a concise report including key comparison charts and tables that the team can use as part of customer communications.

Qualifications & Requirements

Required Skills:

Preferred Skills: Hands on experience with static and dynamic characterization of semiconductor power device

Education Level: MS/PhD student

Field(s) of Study: Semiconductor device physics, GaN, Reliability, WBG applications

Power Integrations is committed to building teams that drive innovation and therefore review a range of factors when determining compensation. The hourly pay range for this internship is $40 to $45. Our pay ranges are determined by role, level, qualifications and work location.

The range displayed on the job posting reflects the minimum and maximum target for this intern in California. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.

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