TD Memory Quality and Reliability PhD Intern

Job Details:

Job Description: 

About the Team 

The Technology Development (TD) Quality and Reliability organization plays a critical role in enabling the successful deployment of next-generation semiconductor technologies through silicon-based quality, reliability, and technology readiness assessments. 

The Memory Quality and Reliability team works closely with Design, Device Engineering, Product Development Engineering (PDE), and Yield organizations to develop, characterize, and certify SRAM, Register File (RF), and Fuse technologies for advanced process nodes. The team supports key technology certification and PDK release milestones through memory characterization, silicon data analysis, predictive modeling, and risk assessment. 

Role Overview 

As a TD Memory Quality and Reliability Intern, you will collaborate with experienced engineers to evaluate advanced memory technologies and help drive technology readiness for future Intel Foundry process nodes. This role offers hands-on experience in memory characterization, silicon data analytics, statistical modeling, and semiconductor technology development. 

You will contribute to projects that support technology certification decisions by analyzing silicon data, developing predictive models, and assessing memory performance across various operating conditions. 

Responsibilities 

Responsibilities may include, but are not limited to: 

• Analyze silicon characterization data from SRAM, Register File (RF), and Fuse memory test structures to identify performance trends, variability, and potential risks. 

• Support memory characterization activities across voltage, temperature, and process conditions. 

• Perform data analysis, visualization, and reporting using Python, JMP, or similar analytical tools. 

• Develop and enhance statistical models for Vmin/Vmax prediction and technology readiness assessments. 

• Support Silicon-to-Simulation (Sil2Sim) correlation studies and memory characterization methodologies. 

• Generate technical reports and contribute to technology certification reviews. 

• Collaborate with cross-functional teams including Design, Device Engineering, Process Integration, Product Development Engineering, and Yield Engineering. 

• Assist with risk assessment activities and technology certification milestones. 

• Present data-driven findings and recommendations to engineering teams and project stakeholders. 

Qualifications:

Minimum Qualifications 

• Currently pursuing a Ph.D. in Electrical Engineering or a related field. 

• Basic knowledge of semiconductor devices, microelectronics, or integrated circuit design. 

• Programming or scripting experience using Python or similar languages. 

• Experience analyzing technical, scientific, or research data through academic projects, research activities, or previous internships. 

• Strong academic performance with a cumulative GPA of 3.0 or higher required.

Preferred Qualifications 

Coursework, research, or experience in one or more of the following areas: 

• SRAM or memory technologies 

• Semiconductor device physics 

• VLSI design 

• Statistics, machine learning, or data science 

• Semiconductor process technology 

Experience with: 

• Python, Pandas, and NumPy 

• JMP or other statistical analysis tools 

• Data visualization and statistical modeling techniques 

• Large-scale data analysis and predictive modeling 

Additional experience in memory architectures, silicon characterization, reliability assessment, or semiconductor test methodologies is highly desirable. 

What You Will Learn 

During this internship, you will gain exposure to: 

• Advanced SRAM, RF, and Fuse memory technologies 

• Memory characterization and certification methodologies 

• Silicon data analytics and statistical modeling techniques 

• Vmin/Vmax evaluation and predictive model development 

• Technology qualification and certification processes 

• Cross-functional semiconductor technology development workflows 

• Silicon-based decision making for technology readiness and risk assessment 

Job Type:

Student / Intern

Shift:

Shift 1 (United States of America)

Primary Location: 

US, California, Folsom

Additional Locations:

US, California, Santa Clara, US, Oregon, Hillsboro

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $120,898.00-120,902.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Our standard internship rates are based on your degree, location, and the job role. Your recruiter can share more about the specific compensation range for your preferred location and job role during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.