Material Science Expert

Location: Global | 100% Remote

Job Type: Contractor | ~15 hours/week

Schedule: Flexible choose your own hours & days Start: Immediate We’re looking for highly skilled Materials Science Experts to contribute to an AI training project involving computational materials science, materials modeling, scientific simulation, and Python. What You’ll Work On Solve and validate computational materials-science problems Create material structures, atomic configurations, compositions & simulation inputs Run atomistic, molecular dynamics, electronic-structure, continuum, electrochemical or related simulations Use Python to automate calculations, generate inputs, analyze results and validate outputs Analyze mechanical, thermal, electrical, chemical, structural and electrochemical properties Diagnose convergence issues, failed calculations, invalid structures and numerical instability Compare computational results with experimental data and literature Review AI-generated solutions for scientific accuracy Develop reproducible reference solutions and verification methods

Required Qualifications: MS or PhD in Materials Science & Engineering, Metallurgy, or related field OR MS/PhD in Mechanical or Chemical Engineering with substantial materials specialization Strong understanding of materials behavior and structure–property relationships Experience in computational materials modeling, simulation, characterization or engineering analysis Strong Python skills Experience with at least one CLI-, scripting-, configuration- or API-based scientific/engineering tool Ability to evaluate modeling assumptions, parameters and convergence criteria Ability to distinguish computational errors from genuine physical behavior Relevant Tools Experience with tools such as LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or equivalent programmatic simulation software. Python experience with Num Py, Sci Py, pandas, Matplotlib, Jupyter, materials informatics libraries or similar tools is valuable. Experience can come from academic research, national laboratories, industry R&D, computational engineering, or demonstrated materials-science work. Selection Process 1 Apply & complete screening questions 2 ~30-minute AI interview 3 Technical assessment, if required 4 Hiring manager review 5 Onboarding & project start Compensation is output-based: Experts are paid per task that meets project specifications. Task completion time may vary based on experience and workflow. Fast Hiring: Roles are typically filled within 48 hours. Selected experts should be ready to begin their first task within 24–48 hours of onboarding.