About the role
Job TitleMaterials Science Expert - AI Trainer
Job TypeContractor (~15 hours per week)
LocationGlobal, fully remote
ScheduleFlexible—you choose the hours and days you work, including weekends if desired The Role We are looking for a highly skilled
Materials Science Expertto contribute to an AI training project involving computational materials science, materials modeling, scientific simulation, and Python. The work involves creating, solving, reviewing, and validating engineering tasks related to material structures, properties, processing, performance, and failure. A representative task may require constructing a material or atomic model, configuring and running a simulation, calculating relevant properties, analyzing the resulting outputs, and determining whether the solution is computationally valid and physically meaningful. This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow.
What You’ll OwnSolve and validate computational materials-science and materials-engineering problems. Create material structures, atomic configurations, compositions, and solver-ready inputs. Model relationships between composition, structure, processing, properties, and performance. Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations. Use Python to generate inputs, automate calculations, conduct parameter sweeps, process results, and validate outputs. What We’re Looking For An MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline; or An MS or PhD in Mechanical Engineering or Chemical Engineering with a substantial materials specialization. Strong understanding of materials behavior and relevant structure-property relationships. Experience with computational materials modeling, simulation, characterization, or materials-focused engineering analysis. Experience using coding agents and Python. Relevant tools may include LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or similar programmatic materials and simulation software. Experience with an equivalent CLI-accessible tool is acceptable. Relevant Python tools may include
NumPy, SciPy, pandas, Matplotlib, Jupyter, atomistic modeling packages, materials informatics libraries, or domain-specific scientific tools. No single library is mandatory. Experience may come from academic research, national laboratories, industry R&D, computational engineering, or other demonstrated materials work. Hiring Process