Project 1: Design Integration and Synthesis Platform to Advance Tightly Coupled
Hybrid Energy Systems (DISPATCHES). This project, in conjunction with the Institute for the Advances Design of Energy Systems (IDAES), is developing novel analysis capabilities through multiscale modeling of energy conversion systems and energy markets. Our work at Notre Dame focuses on creating new computational strategies that integrate optimization-based conceptual design, operations, and control of hybrid energy systems with region-scale cost product models to explore complex interdependencies in the electric grid. Learn more here:
Project 2: Uncertainty Quantification and Optimization with Hybrid Models for Molecular-to-Systems Engineering. This project seeks to establish rigorous mathematical frameworks to quantify the information loss and epistemic uncertainty induced by multiscale model reduction. Hybrid models can overcome this challenge by augmenting physics-based equations with data-driven machine learning constructs (e.g., Gaussian Processes) to quantify the effects of missing, unknown, or simplified physics. We plan to explore many broad applications including reaction engineering, membrane science, and systems biology. Learn more here:
Please write to me at [log in to unmask] to learn more. These projects are well-suited for students with a background outside chemical engineering, i.e., those with an undergraduate degree in math, statistics, computer science, biology, or another engineering discipline.
In addition to my research group, the Computational Molecular Science and Engineering Laboratory (CoMSEL, www.comsel.org) at the University of Notre Dame anticipates opennings for at least ten to fifteen Ph.D. students to start in Fall 2021. Our newly renovated space is home to five research groups in Chemical and Biomolecular Engineering:
CoMSEL is a collaborative research environment with recognized excellence in computational catalysis, molecular simulations, data science, and process systems engineering. We offer Ph.D. students unique training at the intersection of these emerging computational areas of chemistry and chemical engineering, including opportunities to pursue an M.S. in Applied and Computational Mathematics and Statistics or a Graduate Minor in Computational Science and Engineering.
Join the info session on November 10, 12-1 PM EST to learn about our Ph.D. program and how to start the application process. Register at https://cbe.nd.edu/events/cbe-ph-d-program-virtual-info-session/
More information about the Ph.D. program is available at https://cbe.nd.edu/graduate/phd-in-chemical-engineering/