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Computational Mechanics Expert - PhD

Role overview

Qualifications

  • 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

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

Key facts

  • Remote from: India, Germany
  • Part time
  • Research Engineer
  • English

Hard skills

Other skills

  • Problem Solving

About the company

Mercor logo

Mercor

  • Job Boards & Talent Marketplaces
  • 51–200
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

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Job description

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: $70–$85/hour
Location: Remote
Commitment: 15–20 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 20–30 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: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

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

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