Astrophysics Expert - Computational Specialist

mercor - United States - original posting ->
Status
Open
Remote policy
Remote
Employment type
Not stated
Salary
Not stated
Categories
Computational-Astrophysicist, Cosmology, AI-Evaluation-Specialist, Scientific-Problem-Design, Technical-Assessment-Design, Astrophysics-Specialist, Computational-Physics-Specialist, Scientific-Computing-Expert, Scientific-Computing-Specialist, Astronomy-Specialist, Computational-Physicist, Astrophysics-Researcher, Freelance-Astrophysics-Consultant, Astrophysics-Consulting, Astrophysics-Engineer
Source
himalayas
First observed
2026-08-21 08:25 UTC
Last seen
2026-08-21 08:25 UTC
Source claims posted
2026-08-21 07:53 UTC
Consecutive misses
1 of 10

What the posting says

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 Astrophysics & Cosmology Expert

Type:Contract

Compensation:$70–$100/hour

Location:Remote

Commitment:15–20 hours/week

Role Responsibilities

Design challenging computational problems to evaluate AI capabilities in scientific software usage.

Develop problems requiring strategic planning and experimentation to uncover hidden data insights.

Test and refine problems against state-of-the-art AI models to achieve target difficulty.

Utilize Astrophysics & Cosmology expertise with tools like astropy for problem creation.

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

Qualifications

Must-Have

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

Proven proficiency with scientific software libraries through research or professional work.

Strong Python skills for writing problem setups and solution validators.

Ability to work in a Linux/terminal environment with remote compute sandboxes.

Available for 15–20 hours/week.

Preferred

Experience across multiple 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)

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Resources & Support

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

Originally posted on Himalayas

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #235646 2026-08-21 08:25 UTC
    Published
  2. o
    #239125 2026-08-21 10:27 UTC
    Not seen
    Miss 1 in a row