Computational Mechanics Expert - PhD

๐Ÿข mercor ยท all mercor jobs
๐Ÿ“ Germany
๐Ÿ“… Posted 2026-08-13 ยท via Himalayas
๐Ÿท Computational-Mechanics,Structural-Engineering,Scientific-Computing,AI-Research,Mechanical-Engineering,Computational-Physics-Specialist,Computational-Fluid-Dynamics-Specialist,Computational-Physicist,Multibody-Dynamics-Engineer,Computational-Fluid-Dynamics-Engineer,Computational-Materials-Scientist,Computational-Scientist
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About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: Computational Structural & Mechanical Engineering Expert
Type: Contract
Compensation: $70โ€“$85/hour
Location: Remote
Commitment: 15โ€“20 hours/week
Role Responsibilities

- Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.

- Develop problems requiring skilled use of open-source, domain-specific computational tools like FEniCSx/DOLFINx , OpenFOAM , deal.II , and others.

- Evaluate AI models by testing them against state-of-the-art benchmarks and refine problems to achieve the desired difficulty.

- Collaborate with AI research teams to improve problem designs and ensure they test strategic reasoning and problem-solving.

- Work independently and asynchronously to meet deadlines and refine problem designs based on feedback.

Qualifications

Must-Have

- Graduate-level training in a relevant STEM field ( MS, PhD, or equivalent research experience ).

- Proven proficiency with at least one of the listed scientific software libraries through research publications, open-source contributions, or professional work.

- Strong Python skills for writing problem setups, oracle functions, and solution validators.

- Ability to work independently and refine problem designs based on feedback.

- Comfortable working in a Linux/terminal environment with remote compute sandboxes.

Preferred

- Experience across multiple listed domains or tools.

- Familiarity with benchmark or evaluation design.

- Background in scientific teaching or exam/problem-set design.

- Experience with computational reproducibility and containerized environments.

Application Process (Takes 20โ€“30 mins to complete)

- Upload resume

- AI interview based on your resume

- Submit form

Resources & Support

- For details about the interview process and platform information, please check:

- For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Originally posted on Himalayas

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