Postdoctoral Fellow (PREP0004829)

Johns Hopkins University; Baltimore (MD); On-site; USD 65,000 - 85,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to collaborate on a multidisciplinary project advancing nondestructive defect detection metrology for semiconductor packaging. You will develop reference artifacts, benchmark datasets, CAD models, and 3D simulations; automate workflows with Python and prepare results for publication.

The role involves cross-disciplinary teamwork with academic partners and opportunities to present at conferences.

Qualifications

• Doctoral degree in physics, engineering, or related discipline.
• Experience with XCT measurements, reconstruction, and image analysis; XCT simulation is a plus.
• Experience writing Python scripts; API or inter-process communication automation is a plus.
• Strong communication skills and ability to learn quickly.

Responsibilities

• Design 3D models for simulation and run XCT simulations and reconstructions.
• Execute image analysis and organize data sets for publication.
• Prepare samples and perform nondestructive and destructive measurements.
• Present results at internal meetings and with external stakeholders.
• Publish results in journals and present at conferences.

Skills

XCT measurements

Python scripting

Communication skills

Adaptability

Education

Doctoral degree in physics, engineering, or related discipline

Tools

Python

Job description

PREP Research Associate (CHIPS Funded Project)

Position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP).

The role involves collaborating with academic partners on a multidisciplinary project focused on advancing nondestructive defect detection metrology for advanced semiconductor packaging. The incumbent will develop reference artifacts and benchmark datasets, design CAD models, run X-ray computed tomography (XCT) simulations, perform XCT reconstructions, automate workflows with Python, and generate 3D models with seeded defects. The datasets will be used to evaluate defect detection and image segmentation algorithms, including deep learning methods.

Key Responsibilities

• Design 3D models for simulation, run XCT simulations, and carry out XCT reconstruction.
• Execute image analysis and organize data sets for publication.
• Prepare samples and perform nondestructive and destructive measurements.
• Present results at internal meetings and occasional meetings with external stakeholders.
• Publish results in journals and present at conferences.

Qualifications

• Doctoral degree in physics, engineering, or related discipline.
• Experience with XCT measurements, reconstruction, and image analysis; experience with XCT simulation is a plus.
• Experience writing Python scripts; familiarity with automating or controlling other software through APIs or inter-process communication is a plus.
• Experience with sample preparation (mechanical polishing, focused ion beam) or scanning electron microscopy imaging 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.

Preferred

U.S. Citizen status preferred.

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, 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 or demographic characteristics that are irrelevant to the program involved.

EEO is the Law. https://www.eeoc.gov/employees-job-applicants

Salary Range

Minimum and maximum salaries are based on Johns Hopkins University's good faith belief at the time of posting. Compensation offered may vary based on location, skills, experience, internal equity, market conditions, education and training.

Total Rewards

Johns Hopkins offers a total rewards package that supports health, life, career and retirement. More information can be found at https://hr.jhu.edu/benefits-worklife/.