Remote Computational Seismology AI Problem Designer

Mercor; Lacaussade; Sur place; EUR 83 000 - 101 000; Temps partiel

Résumé du poste

Mercor is seeking a Computational Seismology & Geophysics Expert for remote, part-time engagement (15–20 hours/week). You will design challenging computational problems to test AI capabilities in solving scientific tasks and develop problems requiring SPECFEM, ObsPy, and Pyrocko.

You will test and refine problems against state-of-the-art models, collaborate on AI model training and evaluation, and work independently in a Linux/terminal environment to refine designs based on feedback.

Qualifications

• MS/PhD or equivalent research experience in a relevant STEM field.
• Proven proficiency with at least one scientific software library (SPECFEM, ObsPy, etc.).
• 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 to evaluate AI capabilities in solving scientific tasks.
• Develop problems requiring SPECFEM, ObsPy, and Pyrocko.
• Test and refine problems against state-of-the-art AI models to achieve target difficulty.
• Collaborate on AI model training, evaluation, and improvement in computational seismology.
• Work independently and asynchronously to refine problem designs based on feedback.

Connaissances

Python programming

Linux/Terminal

Problem design

Independent work

Formation

MS or PhD in STEM

Outils

SPECFEM

ObsPy

Pyrocko

Description du poste

Mercor is seeking a Computational Seismology & Geophysics Expert for remote, part-time engagement (15–20 hours/week). You will design challenging computational problems to test AI capabilities in solving scientific tasks and develop problems requiring SPECFEM, ObsPy, and Pyrocko.

You will test and refine problems against state-of-the-art models, collaborate on AI model training and evaluation, and work independently in a Linux/terminal environment to refine designs based on feedback.