Post Doctoral Researcher
Artificial Intelligence for Efficient Nondestructive Evaluation of Critical Dimensions of 3D Nanostructures
The researcher will first investigate optimization-based and machine learning-based methods for CD inference of nanofeature arrays. First, the researcher will investigate an optimization-based method for CD inference to improve the method, to assess its ability to converge to the global minimum, and to quantify the uncertainty of the method. Second, the researcher will use neural networks and machine learning-based algorithms to design an AI-based method to estimate CDs of nanofeatures in arrays based on reflectance spectra of the nanofeature arrays.
A Ph.D. in Computer Science, Engineering, Manufacturing, or a related field.
- 5 years of relevant research experience in machine learning.
- Familiarity with multiple scripting languages.
- Ability to develop prototypes of tools needed to analyze data.
- Developing methods to utilize reflectance spectra to estimate the critical dimensions of
nanofeatures.
- Analyzing the convergence and uncertainty of the methods.
- Presenting results at internal meetings, and occasional meetings with external stakeholders.
- Ensuring that results, protocols, software, and documentation have been archived or otherwise
transmitted to the larger organization.