Computational Structural Engineer & Benchmark Designer

Mercor

Paris

À distance

EUR 60 000 - 90 000

Temps partiel

14 jours+
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Résumé du poste

Mercor is seeking a Computational Structural & Mechanical Engineering Expert to design graduate-level problems using open-source tools for AI benchmarks. You will craft tasks that require multi-step workflows, run simulations, and interpret results to uncover hidden information from data.

The role focuses on creative puzzle design, rigorous numerical methods, and manipulation of real workflows with Python-based setups, in a remote-friendly, part-time arrangement.

Qualifications

  • Graduate-level training in STEM fields or equivalent
  • Proven proficiency with at least one listed scientific software libraries
  • Strong Python skills for problem setups, oracle functions, and validators
  • Ability to refine problem designs based on feedback
  • Comfort with Linux/terminal and remote compute sandboxes
  • Available for 15-20 hours per week

Responsabilités

  • Create problems requiring skilled use of specialized scientific software
  • Design graduate-level problems based on real scientific workflows
  • Test problems against state-of-the-art AI models and refine to hit target difficulty
  • Refine problems through multiple iterations and measurements
  • Collaborate with researchers to ensure rigor and reproducibility

Connaissances

Python programming
Finite-element analysis
Multiphysics simulation
Numerical methods
Problem design

Formation

MS or PhD in STEM

Outils

FEniCSx/DOLFINx
OpenFOAM
deal.II
CalculiX
Elmer FEM
Code_Aster
SfePy
FiPy
Pyomo
Cantera

Description du poste

Mercor is seeking a Computational Structural & Mechanical Engineering Expert to design graduate-level problems using open-source tools for AI benchmarks. You will craft tasks that require multi-step workflows, run simulations, and interpret results to uncover hidden information from data.

The role focuses on creative puzzle design, rigorous numerical methods, and manipulation of real workflows with Python-based setups, in a remote-friendly, part-time arrangement.

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