We are looking for Atomistic Materials Modeling Expert candidates for a project delivered through the hiring partner.
What you'll do
- Evaluate advanced scientific problems involving atomistic simulations and computational materials science.
- Review and validate AI-generated answers involving DFT calculations, molecular dynamics, and materials property predictions.
- Assess the appropriateness of computational methods, simulation parameters, convergence criteria, and physical assumptions.
- Analyse atomic structures, electronic properties, reaction energetics, diffusion mechanisms, and materials stability.
- Evaluate surface and interface phenomena, adsorption energies, defect formation, and chemical reaction pathways.
- Develop high-quality reference solutions, evaluation rubrics, and technically rigorous scientific explanations.
- Identify computational inaccuracies, methodological limitations, and errors in scientific reasoning.
- Apply computational expertise to improve AI performance on complex materials science problems.
What you need
- Demonstrated hands-on experience with at least one of the following: Density Functional Theory (DFT), Ab initio Molecular Dynamics (AIMD), Classical Molecular Dynamics (MD), Monte Carlo simulations, Atomistic or first-principles materials modelling.
- Proficiency with one or more computational tools, such as VASP, Quantum ESPRESSO, CP2K, GPAW, LAMMPS, or similar software.
- Strong understanding of electronic structure, interatomic interactions, thermodynamics, statistical mechanics, and materials properties.
- Experience interpreting simulation results and validating computational predictions.
- Strong Python skills for scientific computing, data analysis, or workflow automation.
Nice to have
- Experience with ASE, pymatgen, or computational materials workflow tools.
- Expertise in surface and interface modelling, heterogeneous catalysis, semiconductor materials, or reaction energetics.
- Experience with high-throughput computational materials screening.
- Familiarity with machine-learned interatomic potentials and AI-assisted materials discovery.
- Peer-reviewed publications demonstrating computational materials research.
- Experience integrating experimental materials characterisation with atomistic simulations.
Who you work with
Project and contracting process: the hiring partner. Applications continue on the provider's website.
Pay and hours
This role pays $84/hr, for 40 h/week. The work is remote. That is about 40% above the $60 an hour median for engineering roles open now.
Who can apply from where
The provider lists this role as open worldwide. With a profile, Tier1 checks your country and languages against this role and every other before you apply.