• The Research Fellow will work closely with the Principal Investigator on several research projects on using machine learning in chemical and optimization problems
• The Research Fellow will help to develop machine learning models and control systems for both theory and applications
1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc.
2. The candidates should have strong math, modeling, programming, and scientific writing skills, and prior experience in at least one of the following areas:
a. Chemical process modeling for electrochemical surface engineering processes and/or pharmaceutical crystallization, with expertise in dynamic/data-driven modeling, optimization, Aspen, COMSOL, or CFD
b. Techno-economic analysis (TEA) & life-cycle assessment (LCA) for chemical, energy, or biomanufacturing processes, based on simulation models in Aspen, COMSOL, etc.
c. Control theory & applications — including nonlinear systems, MPC, reinforcement learning, stability analysis, etc.
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