Remote | Computational Mechanics & FEA Expert — $60–$75/hour

We are sharing a specialised part-time consulting opportunity for computational structural and mechanical engineering professionals with graduate-level expertise in numerical simulation, finite-element analysis, computational mechanics, and scientific software.

This role supports the development of advanced AI benchmarks for research-level computational engineering. Selected experts will design original technical problems that require AI systems to use real scientific software, execute simulations, interpret numerical results, plan computational experiments, and reason through complex engineering workflows.

Key Responsibilities

Computational Engineering Problem Design

• Create original graduate-level problems in structural, mechanical, thermal, and computational engineering
• Develop tasks based on realistic scientific and engineering workflows
• Design problems that require multi-step numerical reasoning rather than simple formula application
• Construct tasks with clearly defined setups, expected outputs, and objective validation criteria
• Refine problem difficulty based on model performance and evaluation results

Finite-Element & Structural Mechanics

• Develop computational problems involving beam, plate, and shell analysis
• Work with linear and nonlinear elasticity, continuum mechanics, and solid mechanics
• Design tasks using finite-element and variational formulations
• Incorporate mesh refinement, convergence studies, and numerical verification
• Apply theories such as Euler–Bernoulli and Timoshenko beam formulations where relevant

Scientific Simulation & Numerical Methods

• Build problems requiring specialised open-source scientific software
• Apply finite-element, finite-volume, Galerkin, PDE discretisation, and related numerical methods
• Develop tasks involving constitutive modelling, numerical linear algebra, and nonlinear solution techniques
• Evaluate numerical stability, convergence, accuracy, and modelling assumptions
• Create workflows that reflect genuine computational research practice

Mechanical, Thermal & Multiphysics Modelling

• Design tasks involving computational fluid dynamics and fluid mechanics
• Develop thermal-fluid, heat-transfer, and mass-transfer simulations
• Create problems involving thermodynamics, combustion, and HVAC or thermal systems
• Work with coupled multiphysics simulations and engineering system models
• Develop optimisation, reliability, and manufacturing-simulation problems where relevant

Scientific Software & Solver Workflows

• Apply hands-on expertise with tools such as FEniCSx/DOLFINx, scikit-fem, OpenFOAM, deal.II, MFEM, MOOSE, CalculiX, Elmer FEM, Code_Aster, SfePy, FiPy, Devito, Cantera, CoolProp, Pyomo, or SimPy
• Develop problem setups and reference solutions using domain-specific computational tools
• Work with other open-source structural, mechanical, and scientific solver frameworks where appropriate
• Diagnose solver limitations, numerical edge cases, and implementation failure modes
• Use Python and, where relevant, C, C++, or Fortran-based scientific codes

AI Benchmark Development

• Test computational problems against advanced AI systems
• Analyse whether models can correctly execute scientific workflows and interpret results
• Design tasks where models must strategically choose simulations, measurements, or queries
• Create challenges where hidden information must be inferred from partial computational results
• Iteratively adjust tasks until they achieve the intended level of difficulty and discrimination

Validation & Reproducibility

• Write reference implementations, oracle functions, and solution validators
• Verify that benchmark answers are numerically and scientifically correct
• Ensure computational tasks are reproducible across controlled environments
• Document assumptions, parameters, boundary conditions, and expected outputs clearly
• Work within Linux-based and remote computational environments

Ideal Profile

• Master's degree, PhD, or equivalent research experience in Mechanical Engineering, Structural Engineering, Computational Engineering, Applied Mechanics, or a closely related STEM discipline
• Strong hands-on experience with computational structural or mechanical engineering software
• Proven proficiency with at least one relevant open-source scientific computing or simulation framework
• Professional or research experience using numerical methods to solve real engineering problems
• Strong understanding of finite-element analysis, computational mechanics, PDE-based modelling, or related numerical disciplines
• Strong Python programming skills
• Ability to develop computational setups, reference solutions, and automated validators
• Comfortable working in Linux and terminal-based environments
• Ability to diagnose numerical edge cases, solver failures, and modelling limitations
• Research publications, open-source contributions, or substantial professional simulation work are highly valued
• Experience across multiple computational engineering tools or disciplines is advantageous
• Familiarity with benchmark design, scientific teaching, or advanced problem-set development is beneficial
• Experience with computational reproducibility or containerised environments is advantageous

Engagement Details

• Part-time independent contractor engagement
• Fully remote
• Expected commitment of at least 15–20 hours per week
• Flexible scheduling based on project requirements
• Compensation: $60–$75/hour
• Work involves computational task design, validation, and AI benchmark development
• Projects may be extended, shortened, or concluded based on project needs and performance
• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
• H1-B and STEM OPT support is unavailable for this engagement

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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