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
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
Apply appropriate scientific assumptions and modelling approaches to complex materials problems
Evaluate whether computational results are physically meaningful and consistent with known material behaviour
Scientific Simulation & Property Analysis
Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations
Analyse mechanical, thermal, electrical, chemical, structural, and electrochemical properties
Select and justify simulation parameters, approximations, and convergence criteria
Diagnose failed calculations, invalid structures, numerical instability, and convergence problems
Distinguish genuine physical behaviour from computational artefacts or modelling failures
Python Automation & Reproducible Workflows
Use Python to generate simulation inputs and automate computational workflows
Conduct parameter sweeps, post-process simulation results, and validate outputs
Build reproducible workflows using scripts, configuration files, command-line tools, or programmatic APIs
Work with scientific Python tools such as NumPy, SciPy, pandas, Matplotlib, Jupyter, or comparable libraries
Integrate Python with specialised materials-science or engineering simulation software
Validation, Verification & AI Evaluation
Compare computational results with experimental data, literature values, known material properties, or expected physical trends
Review AI-generated materials-science solutions for scientific correctness
Identify invalid assumptions, configurations, calculations, or conclusions
Develop reproducible reference solutions and objective verification criteria
Document technical reasoning, limitations, and validation methodology clearly
Ideal Profile
MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline
Alternatively, an MS or PhD in Mechanical Engineering or Chemical Engineering with substantial materials specialisation
Strong understanding of materials behaviour and structure-property relationships
Experience with computational materials modelling, simulation, characterisation, or materials-focused engineering analysis
Practical proficiency with Python
Experience with at least one scientific or engineering tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API
Relevant tools may include LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or comparable software
Ability to justify modelling assumptions, simulation parameters, approximations, and convergence criteria
Ability to distinguish computational failures from valid physical phenomena
Strong technical communication skills and ability to explain complex scientific reasoning clearly
Experience may come from academic research, national laboratories, industry R&D, computational engineering, or comparable materials-focused work
Experience limited exclusively to graphical-user-interface workflows is not sufficient for this engagement
Engagement Details
Part-time independent contractor engagement
Fully remote and open to candidates worldwide
Compensation: $80–$130/hour
Expected commitment: approximately 15 hours per week
Schedule is flexible, including the option to work evenings or weekends
Compensation is output-based, with payment made for tasks that meet project specifications
Minimum submission requirements apply
Work will involve computational materials science, scientific simulation, Python automation, numerical validation, and technical review
Selected professionals should be prepared to begin their first task within approximately 24–48 hours of completing onboarding
Roles are typically filled within approximately 48 hours
The selection process may include screening questions, an approximately 30-minute AI interview, and hiring-manager review
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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