Job Details:

Job Description: 

This internship will examine Transformer-based Deep Learning Classification Methods for semiconductor defect dispositioning. In the literature in recent years, Visual Image Transformer-based classification networks have been proposed to provide additional model capabilities beyond what traditional Convolutional Neural Networks can provide. In addition to the possibility of increased accuracy, Transformer-based networks can execute object detection tasks and potentially do so with self-supervised training.

A deliverable from the internship will be to select potential Transformer Networks from the literature and evaluate them alongside the traditional approaches our team employs. The intern can use data sets from established projects. Conditional Classification Models are another area of potential benefit for our defect classification work.

Traditionally, models require retraining in order to contextualize the model for a given produ...