Post-doc positions in computational chemistry, data science and/or applied mathematics, Laboratory of Aurora Clark, University of Utah, USA

The laboratory of Aurora Clark at the University of Utah is looking for two (2) highly-motivated postdoctoral candidates with a background in computational chemistry (classical molecular dynamics, DFT-based MD), data science and/or applied mathematics (e.g., graph theory, computational topology, or machine learning).  

We have several exciting projects focused upon studying the structure and dynamics of soft matter, multicomponent liquids and their interfaces. We are interested in property prediction and learning methods that help understand disorder, reactivity, and transport (see DOI: 10.1021/acscentsci.1c00685 and 10.1039/D0CP00164C). Our group employs a variety of computational chemistry methods combined with applied mathematics (graph, topological data analysis, and geometric measures) to quantify behavior and advance mathematical models of behavior. These systems are studied in the context of separations science, environmental remediation and industrial processing (longstanding areas of expertise), and interface mediated catalysis (NEW).  

# Qualifications 

Highly skilled in molecular dynamics software (LAMMPS, gromacs, CP2K etc.), with extensive script and coding experience. Strong understanding of the chemistry and physics of solution phase processes. Experience with collective variables, transition state theory, and/or metadynamics desired.  

A productive track record with at least three first-author publications is desired alongside excellent communication skills. We seek independent and curious scientists that are willing to bring new skills to the laboratory and learn our methods so that they can tackle challenging scientific questions with rigor.    

# How to apply 

Interested candidates should submit a CV to To learn more about our research program please visit (please be patient as we migrate from WSU to UU web content).   

The University of Utah is an equal opportunity employer.