天体物理专员 - 全远程 | 最高 100 美元/小时
Cosmology Specialist - Fully Remote | Upto $100/hr
Mercor将顶尖的创意和技术人才与领先的AI研究实验室联系起来。公司总部位于旧金山，我们的投资方包括Benchmark、General Catalyst、Peter Thiel、Adam D'Angelo、Larry Summers和Jack Dorsey。
职位：STEM计算科学软件与评估设计 - 天体物理学与宇宙学
类型：合同工
薪资：70–100美元/小时
地点：远程
投入时间：每周15–20小时
岗位职责
- 使用特定领域的科学软件库设计研究生级别的计算问题。
- 评估AI系统解决研究级问题的能力，从查询模拟到解释输出。
- 开发实验策略，从数据中恢复隐藏信息，强调战略推理。
- 根据最先进的AI模型校准任务，优化问题设计以达到目标难度。
- 独立且异步工作，根据校准反馈迭代改进问题设计。
- 使用astropy及相关工具进行宇宙学计算和观测数据处理。
任职要求
必须具备
- 相关STEM领域研究生水平的培训（硕士、博士或同等研究经验）。
- 在科学软件库方面有实际能力，有研究论文或专业工作作为证明。
- 强大的Python编程技能，用于编写问题设置和解决方案验证器。
- 能够在Linux/终端环境中工作，并使用远程计算沙箱。
- 每周至少有15–20小时可用。
优先考虑
- 在多个列出的领域或工具上有经验。
- 熟悉基准测试或评估设计。
- 有科学教学或考试/题集设计背景。
- 有计算可重复性和容器化环境的经验。
申请流程（需20–30分钟完成）
- 上传简历
- 基于简历的AI面试
- 提交表单
资源与支持
- 有关面试流程和平台信息的详细内容，请查看：
- 如有任何帮助或支持，请联系：
备注：我们的团队每天都会审核申请。请完成AI面试和申请步骤，以考虑此机会。
最初发布于Himalayas
查看英文原文
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: STEM Computational Scientific Software & Evaluation Design - Astrophysics & Cosmology
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
- Design graduate-level computational problems using domain-specific scientific software libraries.
- Evaluate AI systems' ability to solve research-grade problems, from querying simulations to interpreting outputs.
- Develop experimental strategies to recover hidden information from data, emphasizing strategic reasoning.
- Calibrate tasks against state-of-the-art AI models, refining problem designs to achieve target difficulty.
- Work independently and asynchronously to iterate on problem designs based on calibration feedback.
- Utilize astropy and related tools for cosmological calculations and observational data reduction.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience).
- Demonstrated proficiency with scientific software libraries, evidenced by research publications or professional work.
- Strong Python programming skills for writing problem setups and solution validators.
- Ability to work in a Linux/terminal environment with remote compute sandboxes.
- 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 pedagogy 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