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. Researchers at NIST collaborate with academic institutions on mutually beneficial projects that require a PREP award. Staff in this role perform technical work that underpins scientific research for 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. Responsibilities include developing reference artifacts and benchmark datasets, designing CAD models, running X-ray computed tomography (XCT) simulations, performing XCT reconstructions, creating Python scripts or packages to automate these processes, and utilizing generative modeling to produce 3D models with seeded defects. The data produced will support the evaluation of defect detection and image segmentation algorithms, including deep-learning approaches.

The incumbent will analyze measurements, conduct image processing, extract meaningful information, organize datasets for publication, communicate with the team, and present findings at conferences and in publications.

• Design 3D models for simulation, run XCT simulations, carry out XCT reconstruction, and execute image analysis.
• Organize and prepare datasets 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; XCT simulation experience is a plus.
• Experience in writing Python scripts; familiarity with automating or controlling other software, tools, or processes through APIs or inter-process communication is a plus.
• Experience with writing Python packages or other programming languages such as C++ or Tcl/Tk is a plus.
• Experience implementing deep learning-based image segmentation processes is a plus.
• Strong oral and written communication skills.
• Ability to quickly learn and adapt to new fields or techniques.

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. The actual compensation offered may vary and depend on factors such as geographic location, skills, work experience, internal equity, market conditions, education, and training.

Johns Hopkins offers a total rewards package that supports health, life, career, and retirement. More information can be found at .

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. The university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or other legally protected characteristics. The university is committed to providing qualified individuals access to all academic and employment programs, benefits, and activities on the basis of demonstrated ability, performance, and merit without regard to personal factors that are irrelevant to the program involved.

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