TD Memory Quality and Reliability PhD Intern

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. 

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 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. 

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 

• 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.

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. 

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