Undergraduate research assistant (CHIPS Funded Project)

Overview

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.

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.

Research Proposal

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.