Geophysics Specialist - Fully Remote | Upto $85/hr
关于工作的职位，默科尔将精英创意和技术人才与领先的人工智能研究实验室联系起来。总部位于旧金山，我们的投资者包括 Benchmark,General Catalyst,Peter Thiel,Adam D'Angelo,Larry Summers 和 Jack Dorsey.职位：计算地震学 &地球物理专家类型：合同补偿：$70 $85/小时 地点：远程承诺：1520小时/周角色责任 ·设计挑战性的计算机问题来评估人工智能能力在解决科学任务中。·开发需要使用 SPECFEM,ObsPy 和 Pyrocko 等专门的科学软件的问题。·测试并对 AI 模型进行检查并改进问题以实现目标难度。· 合作培训，评估和改善人工智能模型的计算地震学。· 在基于反的问题设计上独立和异步工作。· 必须有资格。· 在相关的 STEM 领域 （MS,博士或同等研究经验）的研究生级培训。· 有至少一个科学软件库 （SPECFEM,ObsPy 等）的证明能力。· 强大的 Python 技能用于编写问题设置和解决方案验证器。· 在 Linux/终端环境中独立工作的能力。· 每周可用至少15~20小时。首选 · 多个列表域或工具中的经验。·熟悉基准或评价设计。· 经验在科学教学或考试/问题设计。· 有计算机可复制性和容器化环境的经验。申请过程 （需要20~30分钟才能完成）· 上传简历 · AI 采访根据你的简历 ·提交表格资源 & 支持 · 对面试进程和平台信息，请查看：· 任何帮助或支持，联系：PS:我们的团队每天审查应用程序。请完成你的 AI 采访和申请步骤以考虑这个机会。最初发布于喜马拉雅山。
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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 Seismology & Geophysics Expert
Type:Contract
Compensation:$70–$85/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
- Design challenging computational problems to evaluate AI capabilities in solving scientific tasks.
- Develop problems requiring the use of specialized scientific software like 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.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- 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.
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:
- 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