Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD)
** 薪水：** 每小时45美元到90美元 （美元）. ** 角色标题：** 数学化学，结构生物学和药物发现科学家 （博士学位）** 角色类型：** 承包商 ** 地点：** 远程 （全球）** 工作总结：** 在这个职位中，你将应用自己的专业知识来帮助训练下一代人工智能系统。你的工作将通过高质量的实体输入塑造模型学习，推理和表现的方式。** 主要责任** 1.设计并写计算化学，结构生物和药物探测领域的具有挑战性的专业水平的科学问题，以清晰可验证解决方案。2. 审查和评估人工智能模型的成果以获得科学准确性，严格性和推理深度，识别非专家会错过的微妙错误。3. 在基础上制定了详细的分类和参考答案。4. 在分子建模和仿真，蛋白质结构预测和设计，虚拟选和定位，QSAR/ADMET 建模以及蛋白质学/代谢数据分析等领域应用领域方面的专业知识。5.提供明确的书面解释，以便其他专家能够遵循并验证你的推理。6.通过反复反和同行评审周期满足质量标准。** 要求资格** 1.计算机化学，结构生物学，生物物理，生物信息学，医学化学，生物化学或其他相关领域的博士学位。2. 在学术或工业实验室中实践研究经验 （湿床体验是加分）. 3.专业的书面和口语英语 （C1以上）. ** 优先技能** 01.在药物发现或结构生物学方面的博士后或工业研究经验/生态技术。02. 强的出版记录，特别是有关期刊中的第一作者论文。03.分子建模和仿真：GROMACS,AMBER,NAMD,OpenMM,免费能源方法 (FEP/TI). 04.预测与设计：接和虚拟选：自动定位，滑翔，施雷丁格套件，MOE.06 .化学形式学：RDKit,QSAR/QSPR,ADMET 预测，指纹检测，图书馆设计.07 .蛋白质学与代谢学：LC-MS/MS,MaxQuant, DIA/DDA 工作流程，PTM 分析，非目标代谢学.08 .编程：Python （实践中要求）,加上 R, Bash 或类似；对分子属性预测 ML 的经验是个优点.09 .
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**Pay:** $45-$90 per hour (USD).
**Role Title:** Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD)
**Role Type:** Contractor
**Location:** Remote (Worldwide)
**Job Summary:** In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
**Key Responsibilities**
1. Design and write challenging, expert-level scientific problems in computational chemistry, structural biology, and drug discovery, with clear, verifiable solutions.
2. Review and evaluate AI model outputs for scientific accuracy, rigor, and depth of reasoning, identifying subtle errors that non-specialists would miss.
3. Develop detailed rubrics and reference answers grounded in the primary literature and established methodology.
4. Apply domain expertise across areas such as molecular modeling and simulation, protein structure prediction and design, virtual screening and docking, QSAR/ADMET modeling, and proteomics/metabolomics data analysis.
5. Provide clear written explanations of your reasoning, so that other experts can follow and validate it.
6. Meet quality standards through iterative feedback and peer review cycles.
**Required Qualifications (MUST)**
1. PhD in Computational Chemistry, Structural Biology, Biophysics, Bioinformatics, Medicinal Chemistry, Biochemistry, or a closely related field.
2. Hands-on research experience in an academic or industry lab (wetlab experience is a plus).
3. Professional written and spoken English (C1 or higher).
**Preferred Skills**
01. Postdoctoral or industry research experience (pharma/biotech) in drug discovery or structural biology.
02. Strong publication record, particularly first-author papers in relevant journals.
03. Molecular modeling and simulation: GROMACS, AMBER, NAMD, OpenMM, free energy methods (FEP/TI).
04. Structure prediction and design: AlphaFold, Rosetta, homology modeling, cryo-EM / X-ray crystallography data interpretation.
05. Docking and virtual screening: AutoDock, Glide, Schrödinger Suite, MOE.
06. Cheminformatics: RDKit, QSAR/QSPR, ADMET prediction, fingerprinting, library design.
07. Proteomics and metabolomics: LC-MS/MS, MaxQuant, DIA/DDA workflows, PTM analysis, untargeted metabolomics.
08. Programming: Python (required in practice), plus R, Bash, or similar; experience with ML for molecular property prediction (GNNs, generative models) is a plus.
09. Experience with benchmarking, model evaluation, or scientific writing/reviewing.
10. Ability to explain complex scientific concepts clearly and precisely in writing.