Density Functional Theory is one of the most popular and versatile electronic structure methods available in condensed-matter physics, computational physics, and chemistry. However, like any other theory, DFT is not perfect, and our group is devoted to a better understanding of the underlying limitations of the approximations and possible improvements. One of our primary areas of research is semi-classical DFT, which focuses on finding the leading corrections to local density approximations. A newer approach is machine-learning DFT, where we use machine learning tools to approximate the kinetic energy functional for several simple quantum mechanical systems. Thermal DFT, on the other hand, investigates density functionals at non-zero temperature for use in warm, dense matter. Other directions of research include density-corrected DFT, strong correlation in solids (with Prof. Steve White) and electronic excitations.
Group webpage: http://dft.uci.edu/index.php
If you are interested in theoretical research, then working with Burke group will help you to arm yourself with the necessary mathematical and computational skills and quantum mechanical concepts. You will get to learn Density Functional Theory in a a whole new way and all the stories behind it.
In academic year, the student should commit at least 8-10 hours per week for research.
Kieron Burke, 2145 Natural Sciences II, firstname.lastname@example.org