材料科学专家
Materials Science Expert
Materials Science 专家
薪资：每小时 80–130 美元
地点：全球，远程办公
职位类型：合同工（每周约 15 小时）
时间安排：灵活—您可自行选择工作时间和日期，包括周末
我们正在寻找一位高度专业的 Materials Science 专家，参与一个涉及计算材料科学、材料建模、科学模拟和 Python 的 AI 训练项目。
工作内容包括创建、解决、审查和验证与材料结构、属性、加工、性能和失效相关的工程任务。代表性任务可能需要构建材料或原子模型，配置并运行模拟，计算相关属性，分析结果，并确定解决方案是否在计算上有效且在物理上有意义。
该职位要求具备扎实的材料专业知识以及使用工程或科学工具进行编程的经验。仅限于图形用户界面的经验将不满足要求，因为任务解决方案必须通过代码、脚本、配置文件或命令行工具实现可重复。
您将参与的工作
- 解决并验证计算材料科学和材料工程问题。
- 创建材料结构、原子构型、成分和求解器就绪的输入。
- 建立成分、结构、加工、属性和性能之间的关系。
- 运行原子级、电子结构、分子动力学、连续体、电化学或相关模拟。
- 使用 Python 生成输入、自动化计算、执行参数扫描、处理结果并验证输出。
- 分析机械、热、电、化学、结构或电化学属性。
- 诊断失败的计算、无效结构、收敛问题、数值不稳定性和错误的物理假设。
- 将计算结果与实验数据、文献值、已知属性或预期物理趋势进行比较。
- 审查 AI 生成的解决方案，确保科学正确性，并识别无效假设、配置或结论。
- 开发可重复的参考解决方案和客观的验证方法。
所需资格
- 材料科学与工程、冶金学或相关学科的硕士或博士学历；或
- 机械工程或化学工程的硕士或博士学历，且有显著的材料专业方向。
- 对材料科学有深入理解，熟悉相关计算工具和方法。
查看英文原文
Materials Science Expert
Pay: $80–$130/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 a highly skilled Materials Science Expert to contribute to an AI training project involving computational materials science, materials modeling, scientific simulation, and Python.
The work involves creating, solving, reviewing, and validating engineering tasks related to material structures, properties, processing, performance, and failure. A representative task may require constructing a material or atomic model, configuring and running a simulation, calculating relevant properties, analyzing the resulting outputs, and determining whether the solution is computationally valid and physically meaningful.
This role requires both strong materials expertise and experience using engineering or scientific tools programmatically. Experience limited exclusively to graphical user interfaces will not be sufficient, as task solutions must be reproducible through code, scripts, configuration files, or command-line tools.
What You’ll Work On
- Solve and validate computational materials-science and materials-engineering problems.
- Create material structures, atomic configurations, compositions, and solver-ready inputs.
- Model relationships between composition, structure, processing, properties, and performance.
- Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations.
- Use Python to generate inputs, automate calculations, conduct parameter sweeps, process results, and validate outputs.
- Analyze mechanical, thermal, electrical, chemical, structural, or electrochemical properties.
- Diagnose failed calculations, invalid structures, convergence problems, numerical instability, and incorrect physical assumptions.
- Compare computational results with experimental data, literature values, known properties, or expected physical trends.
- Review AI-generated solutions for scientific correctness and identify invalid assumptions, configurations, or conclusions.
- Develop reproducible reference solutions and objective verification methods.
Required Qualifications
- An MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline; or
- An MS or PhD in Mechanical Engineering or Chemical Engineering with a substantial materials specialization.
- Strong understanding of materials behavior and relevant structure-property relationships.
- Experience with computational materials modeling, simulation, characterization, or materials-focused engineering analysis.
- Practical proficiency with Python.
- Experience with at least one engineering or scientific tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API.
- Ability to understand and justify modeling assumptions, parameters, approximations, and convergence criteria.
- Ability to distinguish computational failures from genuine physical behavior.
- Ability to explain complex scientific reasoning and technical limitations clearly.
Relevant tools may include LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or similar programmatic materials and simulation software. Experience with an equivalent CLI-accessible tool is acceptable.
Relevant Python tools may include NumPy, SciPy, pandas, Matplotlib, Jupyter, atomistic modeling packages, materials informatics libraries, or domain-specific scientific tools. No single library is mandatory.
Experience may come from academic research, national laboratories, industry R&D, computational engineering, or other demonstrated materials work.
Process
- Apply to the role and complete the screening questions.
- Complete an AI interview of approximately 30 minutes.
- Complete a technical assessment, if required.
- 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.
Originally posted on Himalayas