Single-Cell Genomics - Fully Remote | Upto $100/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.位置：生物信息学 &计算单细胞基因组专家类型：合同补偿：$70$100/小时 地点：远程承诺：1520小时/周角色责任 ·设计具有挑战性的 AI 数据问题来评估系统使用真正的科学软件。·开发需要战略规划和多步的工作流进行 AI 模型测试的问题。·通过反复测试对最先进的 AI 模型来改进问题的难度。· 使用扫描，斯克维洛，鱼和古迪等工具进行单细胞 RNA 序列分析，轨迹推理和空间转录学。·独立和异步地工作以满足截止日期并改善问题设计。必须具备资格。·在相关的 STEM 领域 （MS,博士或相应研究经验）学士级培训。·通过研究出版物，开源贡献或专业工作证明了科学软件库的能力。· 写问题的设置，Oracle 函数和解决方案验证器的强大的 Python 技能。·基于反的工作，可以独立工作并完善问题设计。· 舒适在 Linux/终端环境中使用远程计算沙盒。最喜欢的 · 在多个列表域或工具中的经验。· 对基准或评估设计熟悉。· 科学教学或考试/问题设置设计背景。· 数据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 ·基于简历的 AI 面试 ·提交表资源 & 支持 · 请查看有关面试进程和平台信息的详情：· 任何帮助或支持，请联系 PS:我们的团队每天审查应用程序。你可以完成 AI 面试和申请步骤，以便考虑这个机会。
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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: Bioinformatics & Computational Single-Cell Genomics Expert
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
- Design challenging computational problems to evaluate AI systems using real scientific software.
- Develop problems requiring strategic planning and multi-step workflows for AI model testing.
- Refine problem difficulty through iterative testing against state-of-the-art AI models.
- Collaborate on single-cell RNA-seq analysis, trajectory inference, and spatial transcriptomics using tools like scanpy, scvelo, squidpy, and gudhi.
- Work independently and asynchronously to meet deadlines and improve problem designs.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- Proven proficiency with scientific software libraries through research publications, open-source contributions, or professional work.
- Strong Python skills for writing problem setups, oracle functions, and solution validators.
- Ability to work independently and refine problem designs based on feedback.
- Comfortable in a Linux/terminal environment with remote compute sandboxes.
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