出海雷达

STEM Expert (MSc./PhD)

其他限定地区(需当地身份)与中国几乎无重叠,需长期倒时差
公司Micro1
薪资$60 - $120/小时
工作地点United States
地域资格限定地区(需当地身份)
时区要求与中国几乎无重叠,需长期倒时差
用工类型contract
发布时间3 天前
数据来源4dayweek.io
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:与中国几乎无重叠,需长期倒时差。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

** 薪水:** 每小时60美元至120美元 (美元).STEM 专家 ** 薪资:** 60美元每小时120美元 ** 地点:** 全球,完全远程 ** 工作类型:** 承包商 (~15个小时)** 日程:** 灵活你选择你的工作时间和日期,包括周末如果需要 我们正在寻找高技能的 ** STEM 和科学领域专家** 来为涉及技术解决问题,科学的推理,数据分析和 Python 的 AI 培训项目做贡献。这项工作涉及解决,审查和有效地挑战你的专业领域内的具有挑战性的问题。代表性任务可能需要分析科学或数学问题,开发严格的解决方案,使用 Python 进行计算或模拟和评估人工智能生成答案是否技术上正确。**这是一个非常重的编码作用。但有经验在工作流程中使用编码代理的人.**候选人不应该是 STEM 学科的所有专家**.我们正在寻找至少以下领域之一的深入专业知识:1. **化学** 2. **生物学** 3. **数学** 4. **物理** 5. **地球科学 / 地理学 /环境科学** 6. **机器人** 相关科学或量学科也可以考虑,如果考生的专业知识是直接相关的。###你将要做什么 1.解决你专业领域内的复杂的科学,数学或技术问题。2.对人工智能生成的解决方案进行实事,数学和科学的准确审查。3.识别错误的假设,推理错误,缺失的限制和微妙的技术错误。##*要求资格 1.在**至少一个相关的 STEM 或科学领域**强大的专业知识。2.使用 Python 或其他编码语言**的实际能力。3.具有强有力的科学,数学或者数量的问题的解决能力。相关的 Python 工具可能包括**NumPy,SciPy,panda, SymPy,Jupyter**或特定领域的科学图书馆。没有任何特定的 Py Python 图书馆是强制性的。专业知识可以来自学术研究,工业,教学,工程,独立技术工作或其他经验。如果你能够证明在自己的领域具有强大的专业知识,则不必需具体学位或多年的经验.###过程 1.申请角色并完成选问题。2.完成大约30分钟的 AI 面试。3.完成招聘管理员审查。###补偿

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**Pay:** $60-$120 per hour (USD).

STEM Expert

**Pay:** $60–$120/hour

**Location:** Global, fully remote

**Job Type:** Contractor (~15 hours per week)

**Schedule:** Flexible—you choose the hours and days you work, including weekends if desired

We are looking for highly skilled **STEM and scientific-domain experts** to contribute to an AI training project involving technical problem-solving, scientific reasoning, data analysis, and Python.

The work involves solving, reviewing, and validating challenging problems within your area of expertise. A representative task may require analyzing a scientific or mathematical problem, developing a rigorous solution, using Python to perform calculations or simulations, and evaluating whether an AI-generated answer is technically correct.

**This is a very coding heavy role. Candidates but have experience using coding agents in their workflow.**

Candidates are **not expected to be experts across every STEM discipline**. We are looking for deep expertise in at least one of the following areas:

1. **Chemistry**
2. **Biology**
3. **Mathematics**
4. **Physics**
5. **Earth Science / Geoscience / Environmental Science**
6. **Robotics**

Adjacent scientific or quantitative disciplines may also be considered where the candidate's expertise is directly relevant.

### What You’ll Work On

1. Solve complex scientific, mathematical, or technical problems within your domain of expertise.
2. Review AI-generated solutions for factual, mathematical, and scientific correctness.
3. Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes.

### Required Qualifications

1. Strong expertise in **at least one relevant STEM or scientific domain**.
2. Practical proficiency with **Python or other coding languages**.
3. Strong scientific, mathematical, or quantitative problem-solving ability.

Relevant Python tools may include **NumPy, SciPy, pandas, SymPy, Jupyter**, or domain-specific scientific libraries. No particular Python library is mandatory.

Expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or number of years of experience is not strictly required if you can demonstrate strong expertise in your field.

### Process

1. Apply to the role and complete the screening questions.
2. Complete an AI interview of approximately 30 minutes.
3. Complete the hiring manager review.

### Compensation Structure

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply.

### Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

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