General Summary of 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 candidates 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

Special Instructions to Applicants:

Only current UML Employees within the Grants & Contracts (MTA/GRACE) bargaining unit will be considered during the first 10 business days of the posting. All other candidates will be considered after that period.

Initial review of applications will begin immediately and continue until the position is filled. However, the position may close when an adequate number of qualified applications is received.   

This position is contingent upon funding.  The initial appointment will be for ONE year with a possibility of renewal based on productivity, performance and the availability of funding.

Please include a resume, cover letter and research statement with your application. Names and contact information of three references will be required during the application process.