General Summary of Position :
This being an internal opportunity, only current UML Employees, irrespective of Bargaining units are eligible to apply for this position.
Seeking a Postdoctoral Research Associate to conduct computational research on the project related to machine learning algorithm development for boosting multi-scale and multi-physics simulations of catalysis and material science.
Will develop machine learning-based algorithm for plasma catalysis, electrocatalysis, field-enhanced catalysis, as well as non-toxic material discovery using methods such as graph neural networks, gaussian processes, and graph convolutional networks, active learning, and group activity.
The candidate will focus on quantifying the local field strengths, predicting the energetics influenced by fields, and optimizing catalysis and material synthesis processes.
Will help immediate supervisor in writing scholarly articles and proposals and mentor the students. Salary will be competitive and based on experience.
Minimum Qualifications (Required) :
Education :
PhD in Nuclear Engineering, Chemical Engineering, Materials Science, Computer Science, Chemistry, Physics, or related field.
Skills :
- Molecular dynamics simulation
- Electronic structure methods (DFT)
- Microkinetic modeling
- Machine Learning
- High-throughput computing
Additional Considerations :
- Ability to work independently, with limited direction, as well as within a team environment
- Ability to mentor and inspire students with limited research experience
- Experience in heterogeneous catalysis using multi-scale simulation, group activity, and machine learning
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