Synthires
Materials Science Specialist (Remote | $80–$130/hr)
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Materials Science Expert
Type: Contractor — Part-Time
Compensation: $80–$130/hour
Location: Remote — Global
About the Opportunity
micro1 is seeking highly skilled Materials Science Experts to contribute to an AI training project focused on computational materials science, materials modeling, scientific simulation, and Python-based engineering workflows.
You will create, solve, review, and validate technical tasks involving material structures, properties, processing, performance, and failure. Tasks may involve constructing material or atomic models, configuring and running simulations, calculating relevant properties, analyzing outputs, and determining whether solutions are both computationally valid and physically meaningful.
The role requires hands-on materials expertise combined with the ability to use engineering and scientific tools programmatically. Experience limited exclusively to graphical user interfaces is not sufficient, as solutions must be reproducible through code, scripts, configuration files, or command-line workflows.
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, perform parameter sweeps, process results, and validate outputs.
- Analyze mechanical, thermal, electrical, chemical, structural, and electrochemical properties.
- Diagnose failed calculations, invalid structures, convergence issues, numerical instability, and incorrect physical assumptions.
- Compare computational results against experimental data, literature values, known material properties, and expected physical trends.
- Review AI-generated solutions for scientific correctness and identify invalid assumptions, configurations, calculations, or conclusions.
- Develop reproducible reference solutions and objective methods for verifying computational results.
- Clearly explain modeling assumptions, technical limitations, computational findings, and scientific reasoning.
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Required Qualifications
- MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline; or
- MS or PhD in Mechanical Engineering or Chemical Engineering with a substantial materials specialization.
- Strong understanding of materials behavior and structure-property relationships.
- Experience with computational materials modeling, simulation, characterization, or materials-focused engineering analysis.
- Practical proficiency in Python.
- Experience using at least one engineering or scientific tool 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.
- Strong technical communication skills and the ability to explain complex scientific concepts clearly.
Relevant Tools & Technologies
Experience with any comparable programmatic materials or simulation software is acceptable. Relevant tools may include:
- LAMMPS
- ASE
- pymatgen
- Quantum ESPRESSO
- FEniCSx
- CalculiX
- Elmer
- PyBaMM
Relevant Python and scientific computing tools may include:
- NumPy
- SciPy
- pandas
- Matplotlib
- Jupyter
- Atomistic modeling packages
- Materials informatics libraries
- Domain-specific scientific computing tools
No single library or software package is mandatory.
Preferred Qualifications
- Experience conducting computational materials research or engineering analysis.
- Experience in academic research, national laboratories, industrial R&D, computational engineering, or related materials-focused work.
- Familiarity with multiple simulation methodologies or computational materials workflows.
- Experience developing reproducible scientific workflows and automated computational pipelines.
- Experience validating simulation results against experimental or published data.
- Strong background in materials informatics, scientific computing, or simulation-driven engineering.
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Key Areas of Expertise
- Computational Materials Science
- Materials Engineering
- Materials Modeling
- Materials Simulation
- Atomic & Material Structures
- Molecular Dynamics
- Electronic-Structure Modeling
- Continuum Simulation
- Electrochemical Modeling
- Materials Characterization
- Structure-Property Relationships
- Materials Informatics
- Scientific Computing
- Python
- Numerical Analysis
- Engineering Simulation
- AI-Generated Solution Evaluation
- Reproducible Computational Workflows
Compensation & Engagement
Compensation: $80–$130/hour
Engagement Type: Contractor
Expected Commitment: Approximately 15 hours per week
Work Arrangement: Fully remote
Schedule: Flexible — experts can choose their working hours and days, including weekends
Compensation Structure: Output-based; experts are paid per task that meets project specifications
Task completion time may vary depending on experience and workflow. Minimum submission requirements apply.
Application Process
- Apply to the role and complete the screening questions.
- Complete an approximately 30-minute AI interview.
- Complete a technical assessment, if required.
- Complete the hiring manager review.
- Successful candidates proceed through onboarding and begin project tasks.
Start Timeline & Availability
Roles are typically filled within approximately 48 hours. Immediate availability is preferred. Selected experts are expected to begin their first task within 24–48 hours of completing onboarding.
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