
CMOS BEOL Reliability Engineering Intern (Summer 2027)
ROUND LAKE, NYFull-timeSeen todaySeen in employer's feed today
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Job overview
The CMOS BEOL Reliability Engineering Intern will support GlobalFoundries’ Fab 8 Reliability Engineering organization in developing an inline method to assess risks from critical back-end-of-line defects in automotive products. The intern will connect manufacturing defect data with reliability physics to create product-relevant risk metrics and monitoring insights, collaborating with reliability, contamination-free manufacturing, and process integration teams.
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Full job description
About GlobalFoundries GlobalFoundries (GF) is a leading manufacturer of essential semiconductors, enabling AI at scale from the cloud to the physical world. Through deep partnerships with customers, GF delivers differentiated, powe-refficient and high-performance solutions for high-growth markets. GF is a trusted and holistic technology partner for customers around the world. GF's talented, global team remains focused every day on security, longevity and sustainability. For more information, visit www.gf.com. Internship Program Overview: Our Interns & Co-ops are our entry-level talent pipeline for GF across the globe. Our goal is to provide students with a meaningful work experience that will equip them with the skills to embark on a career in the fast-paced and growing semiconductor industry after graduation. As an intern at GF, you'll experience one-on-one mentorship, work assignments that prioritize your growth and potential, professional development opportunities, and the chance to network with executives. Summary of Role: The CMOS BEOL Reliability Engineering Intern will support the Fab 8 Reliability Engineering organization in developing and implementing an inline methodology to assess risks associated with critical back-end-of-line defects in automotive products. Working with Reliability Engineering, Contamination-Free Manufacturing, and Process Integration teams, the intern will connect manufacturing defect data and reliability physics to develop product-relevant defective-parts-per-million risk metrics and actionable monitoring insights. Essential Responsibilities include: Learn the fundamentals of BEOL reliability, semiconductor failure mechanisms, inline defect monitoring, reliability risk assessment, and Failure Modes and Effects Analysis. Analyze inline defect data and scanning electron microscope images to identify and evaluate manufacturing defects that may affect product reliability. Connect observed defect types with potential BEOL degradation mechanisms, including electromigration and time-dependent dielectric breakdown, to assess reliability criticality. Perform statistical analysis to understand key risk drivers and help translate normalized defect density into product-relevant defective-parts-per-million risk estimates. Develop data-analysis and visualization tools or dashboards that communicate defect trends, calculated risk, assumptions, and sensitivity to key inputs. Support development of consistent monitoring methodologies for reliability-critical defects in representative automotive products. Collaborate with Reliability Engineering, Contamination-Free Manufacturing, and Process Integration teams; document methods and results; and communicate project status through reports and presentations. Develop a documented defect catalog linking selected inline defect types to their potential BEOL reliability impact and applicable degradation mechanisms. Deliver a final technical presentation summarizing the inline reliability risk-assessment method, results, limitations, and recommendations for implementation or follow-on work. Other Responsibilities: Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs. Required Qualifications: Education - At least a sophomore at time of application and actively pursuing a Bachelor's, Master's, or PhD in Electrical Engineering, Materials Science, Physics, Chemical Engineering, Mechanical Engineering, Computer Engineering, Data Science, Semiconductor Engineering, or related field through an accredited degree program during the time of internship. Must have at least an overall 3.0 GPA and be in good academic standing. Language Fluency - English (Written & Verbal) Ability to work at least 40 hours per week during the internship. Strong analytical, quantitative, and problem-solving skills. Ability to work independently while collaborating in a cross-functional engineering environmen . Preferred
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