Assistant Research Scientist (PREP0004828)

Johns Hopkins University • Gaithersburg, MD

5d

About The Position

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research. 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 various aspects of the project, including, but not limited to, designing CAD models, running X-ray computed tomography (XCT) simulations, performing XCT reconstructions to generate datasets, preparing samples for FIB/SEM, and nanofabrication. The candidate will develop a Python script or package to automate these processes. Additionally, the candidate will use a team-developed generative modeling process to produce 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.

Requirements

• A master’s degree in physics, engineering, or a related discipline.
• Experience with XCT measurements, reconstruction, and image analysis.
• Experience in writing Python scripts.
• Strong oral and written communication skills.
• Able to quickly learn and adapt to new fields or techniques

Nice To Haves

• Experience with XCT simulation is a plus.
• 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.
• Experience with sample preparation (mechanical polishing, focused ion beam) or scanning electron microscopy imaging is a plus.
• Knowledge of software engineering for AI applications
• Knowledge of mathematical probability and statistics and optimization methods
• Knowledge of machine learning including supervised and unsupervised learning, deep learning, and model evaluation
• Knowledge of dataset biases, and labeling issues
• Knowledge of AI model building
• Knowledge of translating operational needs into solvable AI problems

Responsibilities

• 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.

What This Job Offers

• Career Level: Mid Level