We are sharing a specialised part-time consulting opportunity for experienced materials scientists and engineers with strong expertise in computational materials science, scientific simulation, materials modelling, and Python to contribute to an advanced AI training and engineering evaluation project.
Selected professionals will create, solve, review, and validate technically rigorous materials-science problems involving material structures, properties, processing, performance, and failure. The work combines domain expertise, computational modelling, Python-based automation, numerical validation, and critical review of engineering solutions. Strong experience with programmatic scientific or engineering workflows is essential.
Key Responsibilities
Computational Materials Modelling
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Solve and validate computational materials-science and materials-engineering problems
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Create material structures, atomic configurations, compositions, and solver-ready inputs
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Model relationships between composition, structure, processing, properties, and performance
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Apply appropriate scientific assumptions and modelling approaches to complex materials problems
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Evaluate whether computational results are physically meaningful and consistent with known material behaviour
Scientific Simulation & Property Analysis
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Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations
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Analyse mechanical, thermal, electrical, chemical, structural, and electrochemical properties
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Select and justify simulation parameters, approximations, and convergence criteria
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Diagnose failed calculations, invalid structures, numerical instability, and convergence problems
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Distinguish genuine physical behaviour from computational artefacts or modelling failures
Python Automation & Reproducible Workflows
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Use Python to generate simulation inputs and automate computational workflows
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Conduct parameter sweeps, post-process simulation results, and validate outputs
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Build reproducible workflows using scripts, configuration files, command-line tools, or programmatic APIs
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Work with scientific Python tools such as NumPy, SciPy, pandas, Matplotlib, Jupyter, or comparable libraries
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Integrate Python with specialised materials-science or engineering simulation software
Validation, Verification & AI Evaluation
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Compare computational results with experimental data, literature values, known material properties, or expected physical trends
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Review AI-generated materials-science solutions for scientific correctness
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Identify invalid assumptions, configurations, calculations, or conclusions
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Develop reproducible reference solutions and objective verification criteria
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Document technical reasoning, limitations, and validation methodology clearly
Ideal Profile
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MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline
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Alternatively, an MS or PhD in Mechanical Engineering or Chemical Engineering with substantial materials specialisation
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Strong understanding of materials behaviour and structure-property relationships
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Experience with computational materials modelling, simulation, characterisation, or materials-focused engineering analysis
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Practical proficiency with Python
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Experience with at least one scientific or engineering tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API
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Relevant tools may include LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or comparable software
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Ability to justify modelling assumptions, simulation parameters, approximations, and convergence criteria
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Ability to distinguish computational failures from valid physical phenomena
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Strong technical communication skills and ability to explain complex scientific reasoning clearly
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Experience may come from academic research, national laboratories, industry R&D, computational engineering, or comparable materials-focused work
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Experience limited exclusively to graphical-user-interface workflows is not sufficient for this engagement
Engagement Details
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Part-time independent contractor engagement
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Fully remote and open to candidates worldwide
- Compensation: $80–$130/hour
- Expected commitment: approximately 15 hours per week
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Schedule is flexible, including the option to work evenings or weekends
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Compensation is output-based, with payment made for tasks that meet project specifications
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Minimum submission requirements apply
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Work will involve computational materials science, scientific simulation, Python automation, numerical validation, and technical review
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Selected professionals should be prepared to begin their first task within approximately 24–48 hours of completing onboarding
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Roles are typically filled within approximately 48 hours
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The selection process may include screening questions, an approximately 30-minute AI interview, and hiring-manager review
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, research group, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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