Product Engineering Intern

Qorvo•Greensboro, NC

4d•$31 - $42

About The Position

Qorvo's Internship Program is designed for college students currently enrolled in an accredited Bachelor’s, Master’s, or PhD program. Qorvo offers real work experience, exposure to upper management, and the opportunity to pursue full-time opportunities, as available. Qorvo's Product Engineering Internships are offered in our High Performance Analog, Advanced Cellular, and Connectivity and Sensors business groups. Specific projects and responsibilities will be determined based on the business needs at the time of the internship assignment.

Requirements

Currently pursuing a BS, MS, or PhD in Electrical Engineering or a dual degree in Electrical Engineering and Computer Science
Minimum GPA of 3.0
Analog/RF circuit design coursework and/or experience.
Understanding of power amplifiers/LNAs and their critical performance indicators preferred.
Knowledge of common statistical techniques (CPK, SPC, ANOVA)
Experience with RF measurement equipment such as spectrum analyzers and network analyzers is preferred
Coding coursework and/or experience, preferably with Python and Spark SQL
Basic understanding of AI/Machine Learning techniques for analysis of complex datasets
Detail oriented to ensure design and delivery of high yielding products
Self-starter with strong written and verbal communication skills to convey complex technical information

Nice To Haves

Analog/RF circuit design coursework and/or experience.
Understanding of power amplifiers/LNAs and their critical performance indicators preferred.
Experience with RF measurement equipment such as spectrum analyzers and network analyzers is preferred
Coding coursework and/or experience, preferably with Python and Spark SQL

Responsibilities

Developing innovative techniques to identify yield improvement opportunities in the manufacturing of advanced RFIC products.
Conducting data analysis/mining/extraction utilizing statistical methods and related software tool.
Developing data analysis routines in Python using AI and Machine Learning approaches.
Interfacing with Design, Manufacturing, Test, Applications, Project Management, and Quality Engineering teams to validate your results and conclusions.