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YO AI Labs

Materials Science Expert - Remote. Job in Palo Alto Gr8Jobs

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Job Description

Job Description Job Description Materials Science Expert Role Type:
Contractor Location:
Global, Fully Remote Schedule:
15 hours/week, flexible About the Role We're seeking a Materials Science Expert to support an AI training project involving computational materials science, materials modeling, scientific simulation, and Python. You'll solve, validate, and review materials-engineering tasks and create reproducible, programmatic solutions. No prior AI experience is required. Key Responsibilities Solve and validate computational materials science problems. Build material structures, compositions, and simulation inputs. Run and analyze atomistic, electronic, molecular-dynamics, continuum, or electrochemical simulations. Use Python to automate simulations, parameter sweeps, and data analysis. Analyze mechanical, thermal, electrical, chemical, and structural properties. Diagnose convergence, numerical, modeling, and physical-assumption issues. Compare results with experiments, literature, and expected physical trends. Review AI-generated solutions and develop reliable reference solutions. Required Skills Materials Science & Engineering Computational Materials Modeling Materials Simulation & Analysis Python Scientific Computing Structure-Property Relationships Numerical Validation & Troubleshooting Technical Problem-Solving Tools Experience with tools such as LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM , or equivalent CLI/API-based software. Familiarity with NumPy, SciPy, pandas, Matplotlib, or Jupyter is beneficial. Qualifications MS/PhD in Materials Science, Metallurgy, or related field; or Mechanical/Chemical Engineering with strong materials specialization. Experience in computational materials modeling, simulation, characterization, or materials R D. Strong Python and programmatic engineering-tool experience. Ability to explain modeling assumptions, validate results, and distinguish computational errors from physical behavior.
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