Postdoctoral Fellow

General Description

PREP Research Associate
CHIPS Funded Project

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, and thus requires that such institutions be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Reliability Testing and Failure Analysis for Advanced Semiconductor Packaging

The work will entail:

The Infrastructure Materials Group at the National Institute of Standards and Technology seeks a researcher with demonstrated knowledge of reliability testing and failure analysis for advanced semiconductor packaging, with strength in polymeric materials and multilayer interfacial mechanics relevant to CHIPS applications. The successful candidate will integrate reliability modeling with experimental techniques to investigate how environmental stressors accelerate aging, property degradation, and failure mechanisms in complex package architectures. The position requires expertise in mechanical characterization of thin-film and multilayer interfaces, including adhesion and failure onset, as well as a deep understanding of polymer structure-property relationships and failure analysis.

If selected, the researcher will play a significant role in NIST projects focused on reliability testing and failure analysis for advanced packaging. Collaborating with NIST staff and external partners, the researcher will design and execute experimental research to assess the impact of stress on the mechanical and thermal properties of polymeric materials and interfaces used in advanced packages. The research will aim to identify and quantify failure mechanisms, such as interfacial delamination, cohesive cracking, and fatigue damage, and generate high-quality datasets for model calibration and validation. These datasets will, in turn, inform the development of more accurate long-term reliability prediction frameworks. Ultimately, the outcomes of this research will provide a scientific foundation for the development of test methods, materials selection, and quality assurance protocols for the semiconductor packaging industry, driving advancements in product reliability and performance.

• Develop and validate new test methods for multilayer adhesion in advanced packaging assemblies.
• Characterize the thermal and mechanical properties of materials and interfaces before, during, and after accelerated aging.
• Conduct in-situ environmental digital image correlation (DIC) to quantify package/assembly deformation during thermal cycling.
• Develop advanced failure-analysis methods using microscopic and X-ray-based techniques for complex package structures.
• Perform finite element analysis to simulate package deformation/warpage under thermo-mechanical loading, informing the development of more accurate reliability models.
• Create comprehensive datasets of material and interface properties, both pre- and post-aging, to support reliability modeling.
• Communicate results through conference presentations, peer-reviewed publications, and technical reports.

Qualifications

• Live in the United States
• Ph.D. in Materials Science / Mechanical Engineering / Electrical Engineering /Physics/Chemical Engineering/Chemistry
• Strong oral and written communication skills
• Experience in polymeric thin film adhesion
• Experience in advanced semiconductor packaging is preferred
• U.S. citizenship is preferred

Application Instructions

Please upload the following with your application:

• CV/Resume

*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. *Your resume will not be considered if the following information is included on your CV/resume.***

• Self portraits
• Phone number
• Home address/Country
• Citizenship status
• Languages spoken
• Sex/Gender