Postdoctoral Fellow; PREP

PREP Research Associate

CHIPS Funded Project.

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST encourages collaboration with academic researchers by granting PREP awards to institutions. The PREP program requires staff from varied backgrounds to contribute to scientific research across many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Research Engineer (CHIPS Project: Nondestructive defect detection metrology for advanced semiconductor packaging)

The candidate will join a multidisciplinary team of scientists working to advance nondestructive defect detection metrology for advanced semiconductor packaging by developing reference artifacts and benchmark datasets. The candidate will contribute to designing CAD models, running X‑ray computed tomography (XCT) simulations, and performing XCT reconstructions to generate datasets. The candidate will develop a Python script or package to automate these processes.

Additionally, the candidate will utilize a generative modeling process created by the team to help generate 3D models with seeded defects. The datasets will be used to evaluate defect detection and image segmentation algorithms, including those based on deep learning principles. The incumbent will analyze the resulting measurements, perform image processing, and extract meaningful information to support the research goals outlined in the experiment plan.

They will organize the measured and analyzed datasets for publication, communicate with the team, and share the results at conferences and in publications.

• Design 3D models for simulation, run XCT simulations, carry out XCT reconstruction, and execute image analysis.
• Organize and prepare data sets for publication.
• Present results at internal meetings and occasional meetings with external stakeholders.
• Publish results in journals and present results at conferences.

• A doctoral degree in physics, engineering, or a related discipline.
• Experience with XCT measurements, reconstruction, and image analysis. Experience with XCT simulation is a plus.
• Experience in writing Python scripts. Familiarity with automating or controlling other software, tools, or processes through APIs, inter-process communication, or similar methods is a plus.
• Experience in writing Python packages or with other programming languages like C++ or Tcl/Tk is a plus.
• Experience with implementing deep learning‑based image segmentation processes is a plus.
• Strong oral and written communication skills.
• Able to quickly learn and adapt to new fields or techniques.

Please upload the following with your application:

• CV/Resume (limit to 3 pages; include a valid email address. Exclude any of the following: name, address, contact info, work history, education, skills, accomplishments, references.)
• Self portraits
• Phone number
• Home address/Country
• Citizenship status
• Languages spoken
• Sex/Gender

All submissions will be reviewed to determine eligibility and to meet programmatic requirements. By applying, you acknowledge that participation requires signing a Non‑Disclosure Agreement prior to beginning any work.