Computational Materials Scientist - AI Trainer

Salary: $332,800 - 374,400 per year Requirements:

• We require a masters or PhD in Materials Science, Computational Chemistry, Physics, Computer Science, or a closely related quantitative field.
• We look for at least one first-author publication in a peer-reviewed journal.
• We require demonstrated expertise in both machine learning and computational materials science, including areas such as DFT, force fields, atomistic simulation, or materials informatics.
• We value strong independent problem-solving ability.
• Additional experience with computational science teaching, materials ML frameworks such as CGCNN, MatGL, M3GNet, or ALIGNN, and simulation tools such as VASP, Quantum ESPRESSO, LAMMPS, or ASE is helpful.

• We build, train, and evaluate models using simulation data from DFT, molecular dynamics, or Monte Carlo methods.
• We apply supervised and unsupervised learning to property prediction, materials discovery, and structure–property relationships.
• We connect materials informatics workflows with high-throughput computational pipelines.
• We document methods, assumptions, and technical decisions so results can be reproduced.

• AI
• Machine Learning

More:

We are AfterQuery, and we develop expert datasets and experiments that advance AI research. This is a fully remote, asynchronous contract focused on training AI models for computational materials research using real atomistic, electronic, and structural datasets. The role is approximately 10 hours per week, starts ASAP, and is project based, with individual assignments typically running 2 to 3 weeks and hours agreed for each accepted project. The work offers the chance to apply your research judgment to challenging materials problems while building your technical portfolio. The engagement is listed as a contract role with hourly pay of $160 to $180.

last updated 39 week of 2026