Postdoctoral Research Associate - High-Throughput Discovery of Correlated High-Entropy and Topological Materials

University of North Texas System • Denton, TX

7d • Onsite

About The Position

The University of North Texas Department of Physics seeks a postdoctoral researcher for an NSF-funded Designing Materials to Revolutionize and Engineer our Future (DMREF) collaboration. The project builds a closed theory–experiment loop to discover correlated high-entropy materials and their quantum properties. High-throughput computation proposes candidate systems, experimental collaborators synthesize and characterize them, and those results inform more accurate calculations and broader computed properties. Data will be maintained in a shared repository, updated in real time, and released publicly at the project’s conclusion, with the goal of integration into databases such as AFLOW.

The postdoctoral researcher will extend PAOFLOW, a software suite that builds tight-binding Hamiltonians from projections of DFT wavefunctions onto atomic orbitals and computes properties including Berry-curvature effects, transport, optical response, and topological invariants. A central project goal is to move beyond ideal crystals to realistic compositionally disordered materials by assembling large supercell Hamiltonians from small graph-prototype cells in a local-orbital basis, extending ab initio accuracy to nanometer-to-micrometer length scales.

The appointment is for one year. The start date is flexible, and compensation is competitive and commensurate with qualifications, experience, discipline, university guidelines, and available funding. The work schedule varies based on assignment. Applicants should submit a cover letter, CV with publication list, a research-interests statement of no more than two pages, and contact information for three references.

Requirements

• Ph.D. in physics, materials science, chemistry, or a related field, conferred by the start date.
• Demonstrated experience with plane-wave DFT codes; Quantum ESPRESSO is preferred.
• Experience with the electronic structure of solids.
• Strong Python skills.
• Experience with scientific software development and large-scale calculations on HPC clusters.
• Strong publication record.
• Ability to work in an interdisciplinary team with experimentalists.

Nice To Haves

• Experience with tight-binding or Wannier-type methods, topological materials, or Berry-curvature-derived properties.
• Experience with high-throughput workflows, materials databases, or machine learning for materials.
• Familiarity with GPU/parallel Python or modeling disorder and alloys.

Responsibilities

• Develop and implement methods for disordered and high-entropy systems in the PAOFLOW framework, including Hamiltonian construction from graph prototypes and validation against full DFT.
• Run and automate high-throughput DFT+U+V (ACBN0/eACBN0) screening on leading HPC systems.
• Compute electronic, optical, anomalous and spin transport, and topological properties, including Berry curvature, anomalous/spin Hall conductivity, spin texture, quantum oscillations, and superconductivity; compare results directly with experimental data.
• Quantify errors and uncertainty in theoretical predictions and design remediation strategies so calculations can guide synthesis decisions.
• Maintain the data repository and feedback workflow with experimental collaborators.
• Publish and present research, release open-source software, and help mentor students.

Benefits

• Benefits are offered; details are available through the UNT System Benefits information.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree