Postdoctoral Associate, Computational Condensed Matter / Materials Physics, UMKC School of Science and Engineering

University of Missouri System • Kansas City, MO

26d

About The Position

The University of Missouri - Kansas City invites applications for a Postdoctoral Associate in computational condensed matter and materials physics. The successful candidate will lead theory/modeling efforts on semiconductor fabrication and bonding simulations, working closely with Prof. Paul Rulis. The position offers access to state-of-the-art high-performance computing resources and opportunities for cross-disciplinary collaboration. This is a 12-month, full-time, benefit eligible, unranked academic position.

Requirements

• Ph.D. in Physics, Materials Science, Chemistry, Applied Physics, or a related field by the start date.
• Demonstrated research experience in computational condensed matter/materials (e.g., electronic structure, lattice dynamics, defects, transport, magnetism, excitations).
• Proficiency with at least one major simulation package (e.g., VASP, Quantum ESPRESSO, ABINIT, GPAW, WIEN2k, LAMMPS, CP2K, OLCAO).
• Strong programming skills (e.g., Python, Perl, and Fortran), scripting, and Linux HPC workflows (job schedulers).

Nice To Haves

• Experience with beyond-DFT methods (e.g., GW/BSE, DMFT, QMC) or machine-learning interatomic potentials (e.g., GAP, SNAP, DeePMD, MACE, NequIP).
• Familiarity with workflow frameworks (e.g., ASE, pymatgen, custodian, FireWorks, atomate, AiiDA, AFLOW) and databases (Materials Project, OQMD, NOMAD).
• Background in phonons/thermal transport, spin textures/magnetism, defects and dopants, electrocatalysis, or interfaces/heterostructures.
• Good software engineering practices (Git, CI, containers, reproducible environments) and data stewardship (FAIR principles).
• Experience collaborating with experimentalists and translating predictions into measurements.

Responsibilities

• Design and execute computational studies using first-principles and/or atomistic methods (e.g., DFT and classical/ab initio MD).
• Develop and apply workflow automation and data/pipeline tools for high-throughput screening and data generation.
• Analyze structure-property relationships and generate testable predictions to guide experiments.
• Write manuscripts, present at conferences, and contribute to proposals and reports.
• Maintain reproducible code and documentation (version control, unit tests, containers).
• Co-mentor graduate/undergraduate researchers and contribute to group seminars.

Benefits

• The University of Missouri provides generous leave, health plans, and retirement contributions that add to your bottom line.
• As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses.

What This Job Offers

• Job Type: Full-time
• Industry: Educational Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees