Single-Cell Genomics Expert - 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.职位：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 ·设计挑战性的计算机问题来评估人工智能能力在科学研究中。·创造需要熟练使用扫描，斯克维洛，卡马里 py 和古迪等专门的科学软件的问题。· 测试和精炼与最先进的 AI 模型来实现目标难度。· 开发需要战略规划和有效缩小可能性的问题。· 在基于反的基础上独立工作，以精细化问题设计。资格必须有。· 在相关 STEM 领域 （MS,博士或相等研究经验）的毕业生级培训。· 有至少一个列出的科学软件库的证明能力。· 强大的 Python 技能。· 能够独立工作并精细化问题的设计。· 在 Linux/终端环境中舒适工作。首选 · 在列出的多个域或工具中体验。·熟悉基准或评估设计。· 科学教学或考试/问题组设计的背景。· 有计算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 面试根据你的简历 ·提交表格资源 & 支持 · 对面试进程和平台信息详细，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 面试和申请步骤将被考虑为此机会。原始地发布在喜马拉雅山。
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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: 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 capabilities in scientific research.
- Create problems requiring skilled use of specialized scientific software like scanpy, scvelo, squidpy, and gudhi.
- Test and refine problems against state-of-the-art AI models to achieve target difficulty.
- Develop problems that require strategic planning and efficient narrowing of possibilities.
- Work independently 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 of the listed scientific software libraries.
- Strong Python skills.
- Ability to work independently and refine problem designs.
- Comfortable working in a Linux/terminal environment.
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