This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. 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.
Research Title:
Undergraduate research assistant
The work will entail:
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 the design of CAD models, run X-ray computed tomography/laminography (XCT/XCL) simulations, and perform XCT reconstructions to generate datasets. The candidate will support the development of a Python package to help automate these processes. The candidate may contribute to improving the surface meshing and voxel image conversion processes. The datasets will be used to evaluate defect detection and image segmentation algorithms, including those based on deep learning principles.
Candidates must be eligible to obtain a Department of Commerce background check for facility access.
Key responsibilities will include but are not limited to:
- Developing a Python package to help automate the creation of CAD models, generation of ground truth images, running XCT/XCL simulation software, and performing XCT reconstructions.
- Updating and maintaining codes in a GitLab repository.
- Using the software developed to create ground truth models and XCT reconstructions of them.
- Optimizing XCT reconstructions through adjustment of image acquisition parameters in the XCT simulation software.
Qualifications
- Current undergraduate student majoring in Computer Science, Engineering, Physics, or a related field.
- Familiarity with Python modular programming and use of configuration files.
- Experience with Git.
- Experience with running X-ray simulation software (e.g., aRTist).
- Experience with image processing and segmentation.
- Able to quickly learn and adapt to new fields or techniques
- Strong oral and written communication skills.
The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.