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David Broniatowski

6 months ago

Post-Doctoral Fellow in Physics-Informed Machine Learning for Semiconductor Process Modeling George Washington University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Post-doctoral fellow position associated with the George Washington University and NIST under the CHIPS Act mission. The post does not specify stipend, salary, tuition, or other financial details.

Deadline

Expired

Country flag

Country

United States

University

George Washington University

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Keywords

Computer Science
Chemistry
Chemical Engineering
Materials Science
Mathematics
Python Programming
Uncertainty Analysis
Digital Twin Technology
Multiscale Modeling
Atomic Layer Deposition
Computational Modelling
Physics

About this position

George Washington University and NIST are seeking a Post-Doctoral Fellow in Physics-Informed Machine Learning (PIML) for semiconductor process modeling in Gaithersburg, Maryland.

The project sits at the intersection of physics, chemistry, computer science, materials science, and mathematics, with a strong focus on atomic layer deposition (ALD), multiscale modeling, and high-fidelity digital twins for chip manufacturing. The role is tied to the CHIPS Act mission to accelerate semiconductor innovation.

Responsibilities include designing and training PIML models constrained by physical laws, developing multiscale simulations from the atomic level upward, implementing and evaluating algorithms, quantifying uncertainty, and building robust Python software tools. The fellow is also expected to present at international conferences and publish in high-impact journals.

Eligibility highlights: a Ph.D. in Chemistry, Physics, Math, Computer Science, or Data Science; familiarity with TensorFlow or PyTorch; experience with process modeling tools such as Cantera or CHEMKIN; strong Python programming skills; and the ability to work with heterogeneous data and uncertainty analysis.

This is a postdoctoral opening, not a scholarship. No stipend or salary amount is stated in the post. The application link is provided in the post, and no deadline is mentioned.

Funding details

Post-doctoral fellow position associated with the George Washington University and NIST under the CHIPS Act mission. The post does not specify stipend, salary, tuition, or other financial details.

What's required

Ph.D. in Chemistry, Physics, Math, Computer Science, or Data Science. Applicants should be familiar with TensorFlow or PyTorch, have experience with process modeling packages such as Cantera or CHEMKIN, be strong in Python for computational modeling, and be able to analyze heterogeneous data sources and assess prediction uncertainty.

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Professors

Professor of Engineering Management and Systems Engineering

University Name
Country flag

United States

Research Interests

Artificial Intelligence

Statistics

Physics

Materials Science

Computer Science