Materials Researcher | Remote

Position: Materials Science Expert Type: Contract Compensation: $80 - $130/hour Location: Remote Commitment: 10-40 hrs/week Role Responsibilities Solve 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. Analyze mechanical, thermal, electrical, chemical, structural, or electrochemical properties. Diagnose failed calculations, invalid structures, convergence problems, numerical instability, and incorrect physical assumptions. Compare computational results with experimental data, literature values, known properties, or expected physical trends. Review AI-generated solutions for scientific correctness and identify invalid assumptions, configurations, or conclusions. Develop reproducible reference solutions and objective verification methods. Requirements An MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline. 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. Practical proficiency with Python. Experience with at least one engineering or scientific tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API. Ability to understand and justify modeling assumptions, parameters, approximations, and convergence criteria. Ability to distinguish computational failures from genuine physical behavior. Ability to explain complex scientific reasoning and technical limitations clearly. Experience with tools like LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or similar programmatic materials and simulation software. Application Process Easy Apply on LinkedIn Check email for next steps Participate in resume evaluation & interview stage

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