Doctoral Student in Computational Materials Design: Carbon- and Oxygen-Based Conductors

This PhD position at Chalmers University of Technology focuses on computational materials design to create conductive materials from carbon and oxygen—elements abundant on Earth. The project aims to predict and synthesize new classes of one-dimensional metallic conductors, potentially superconductors, by leveraging crystal-structure prediction algorithms and periodic Density Functional Theory (DFT). The successful candidate will collaborate closely with experimental researchers to validate theoretical predictions through synthesis and characterization. The work involves advanced computational techniques, scripting, and a strong theory-experiment feedback loop, with potential extensions into superconductivity, magnetism, or transport modeling. The position is based in Gothenburg, Sweden, within a dynamic, interdisciplinary research environment.

• Use crystal-structure prediction algorithms and periodic Density Functional Theory (DFT) to identify stable phases of oxocarbon radical anions across various counterions.
• Assess candidates by thermodynamic and dynamic stability, and quantify electronic transport descriptors such as band dispersion, density of states, and stacking distance.
• Collaborate closely with experimental researchers to synthesize and characterize predicted materials, validating theoretical predictions.
• Develop chemical design rules for new conducting materials, with potential extensions into superconductivity, magnetism, or transport modeling.
• Present research findings at seminars, conferences, and publish results in peer-reviewed journals.
• Teach at the undergraduate level or perform departmental duties up to 20% of working hours.