Postdoctoral Fellow; PREP

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 recipients 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.

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.
• Presenting 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 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

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

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