Computational Materials Scientist (Xora Portfolio Company)

We are seeking a Computational Materials Scientist with expertise in either battery materials (solid/liquid electrolytes) or semi-conductors or catalysis. Elemynt is a computational materials research platform provider that works at the intersection of AI/ML, physics, and data-driven materials design. At Elemynt, the candidate is expected to be hands-on combining state-of-the-art ML interatomic potentials (MLIPs) with atomistic simulations to accelerate materials discovery.ResponsibilitiesApply MLIPs (MACE, M3GNet, NequIP, GAP) to predict properties of materialsRun atomistic simulations using DFT codes (VASP, Quantum ESPRESSO, CASTEP, etc.) and MD packages (LAMMPS, GROMACS, etc.)Implement graph neural networks and diffusion models to generate and optimize electrolyte candidatesPerform synthesis prediction and precursor selection, linking atomistic modeling to experimental feasibilityCurate and query large-scale materials and reaction databases for training and validationCollaborate with experimental teams to validate predictions and feed results back into automated workflowsRequirementsPhD in Materials Science, Chemistry, Physics, or related fieldDemonstrated experience with MLIPs (MACE, M3GNet, NequIP, etc.)Proficiency with DFT codes (VASP, QE, CASTEP, etc.) and MD engines (LAMMPS, GROMACS, etc.)Experience with ASE, pymatgen or similar toolkits for job setup/automationStrong skills in Python and building scientific workflowsKnowledge of synthesis prediction, precursor selection, or cheminformaticsStrong database and automation framework skills (Fireworks, Jobflow, Atomate, Airflow, Temporal)