Crossing Hurdles
Materials Science Expert
United Kingdom
$80 – $130/hr
Posted about 22 hours ago
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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.
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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.
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Skills
Computational Materials Science
Python
Materials Modeling
Simulation
Atomic Configurations
Electronic-structure Simulation
Molecular Dynamics
Electrochemical Analysis
Data Validation
Scientific Reasoning
CLI Tooling
Materials Engineering
Location