Remote Computational Seismology AI Challenge Designer

Mercor

Lacaussade

Sur place

EUR 83 000 - 100 000

Plein temps

14 jours+
Générateur de candidature

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Résumé du poste

Mercor is seeking a Computational Seismology & Geophysics Expert for a remote contract role. The position entails designing and refining AI-driven computational problems, with 15–20 hours weekly commitment.

You will work asynchronously to test and validate multi-step workflows using scientific software and Python. Ideal candidates hold MS/PhD or equivalent research experience, strong Python skills, and proficiency with scientific libraries in a Linux environment.

Qualifications

  • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
  • Proven proficiency with at least one scientific software library.
  • Strong Python skills for writing problem setups and solution validators.
  • Ability to work independently in a Linux/terminal environment.
  • Available for at least 15–20 hours per week.

Responsabilités

  • Design challenging computational problems using scientific software to test AI capabilities.
  • Develop problems requiring AI to compute exact answers from complex, multi-step workflows.
  • Create tasks where AI must strategically plan queries or experiments to uncover hidden information.
  • Refine problems through testing loops against state-of-the-art AI models to achieve target difficulty.
  • Work independently and asynchronously to refine problem designs based on feedback.

Connaissances

Python
Linux
Scientific libraries

Formation

MS/PhD or equivalent

Description du poste

Mercor is seeking a Computational Seismology & Geophysics Expert for a remote contract role. The position entails designing and refining AI-driven computational problems, with 15–20 hours weekly commitment.

You will work asynchronously to test and validate multi-step workflows using scientific software and Python. Ideal candidates hold MS/PhD or equivalent research experience, strong Python skills, and proficiency with scientific libraries in a Linux environment.

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