We invite applications for a joint postdoc position at the Universities of Minnesota (UMN) and North Dakota (UND) on the study of MAB phases (which are atomically laminated, ternary transition metal borides) using Density Functional Theory, machine learning, and Dynamical Mean Field Theory.

Requirements:
• A Ph.D. in the physical sciences (physics, chemistry, or materials),
• Familiarity with programming (such as Python)
• Expert knowledge of first-principles calculations using DFT (VASP etc.)
• Experience in crystal structure prediction and high-throughput calculations

Other desirable skills:
• Experience in the (or willingness to learn) first-principles many-body approaches (especially DFT+DMFT) and machine learning.
• Experience in electrochemistry (such as constructing Pourbaix diagrams).

The postdoc is going to work with the groups of Deniz Cakir (UND) and Turan Birol (UMN) simultaneously and must possess collaborative skills to work with experimentalists as well. Highly motivated candidates are encouraged to apply by sending their CV and a list of two referees to Deniz Cakir [email protected] and Turan Birol [email protected]. Review of applications will begin immediately and continue until the position is filled.