AI Drug Discovery Scientist (Ph.D. or M.S.)

Full Description

We are seeking a talented AI Drug Discovery Scientist with a strong background in computer science, machine learning, and computational modeling to join our innovative drug discovery team. The candidate will be responsible for developing AI models and databases for molecular design, compound screening, and mechanism prediction.

具有计算机科学或人工智能背景，并熟悉生物、化学领域的博士或硕士候选人将优先。您将参与 AI 模型搭建、药物分子生成算法开发、以及结构–活性关系（SAR）数据库构建与管理，推动公司AI制药平台的研发闭环。

Key Responsibilities / 主要职责

• Develop and implement machine learning and deep learning models for molecular generation, property prediction, and virtual screening. 负责药物分子生成、性质预测、虚拟筛选等AI模型的设计与实现。

• Build, clean, and manage multi-dimensional biological and chemical databases. 进行多维度生物与化学数据库的建立、整理与维护。

• Integrate cheminformatics, bioinformatics, and omics data for predictive model training. 融合化学信息学、生物信息学及多组学数据进行AI建模。

• Collaborate with medicinal chemists and biologists to validate model predictions and optimize compound design. 与化学、生物团队合作验证模型预测并优化化合物设计。

• Design and document computational workflows, pipelines, and data visualization dashboards. 设计和记录AI建模工作流程，并开发可视化界面。

• Publish findings, contribute to patents, and support external collaborations. 发表科研成果，参与专利申请及国际合作。

Required Qualifications / 任职要求

• Ph.D. or M.S. in Computer Science, Computational Biology, Bioinformatics, Data Science, or related field. 计算机科学、计算生物学、生物信息学、数据科学或相关专业博士或硕士学位。

• Strong proficiency in Python and frameworks such as PyTorch, TensorFlow, or Scikit-learn. 精通Python及主流AI框架（PyTorch、TensorFlow、Scikit-learn等）。

• Experience in data preprocessing, feature engineering, and model evaluation. 熟悉数据预处理、特征工程与模型评估。

• Familiarity with cheminformatics or molecular representation learning (SMILES, graph neural networks, etc.). 熟悉化学信息学或分子表示学习（如SMILES、图神经网络等）。

• Ability to work in an interdisciplinary environment combining chemistry, biology, and AI. 能在化学、生物与人工智能交叉的环境中开展研究。

• Good English communication and writing skills. 具备良好的英文沟通与写作能力。

Preferred Qualifications / 优先条件

• Experience in AI-driven drug discovery, virtual screening, or QSAR modeling. 具备AI驱动的药物发现、虚拟筛选或QSAR建模经验。

• Background in medicinal chemistry, molecular docking, or pharmacophore modeling. 具有药物化学、分子对接或药效团建模背景。

• Experience with large-scale database management (SQL/NoSQL) and cloud computing environments. 熟悉大型数据库管理（SQL/NoSQL）及云计算平台。

• Track record of publications or patents in relevant fields. 在相关领域有发表论文或专利经验者优先。

Application Details

Applicants Should Submit

• Curriculum vitae.

• Cover letter.

• Name and contacts of 2 referees.

Submit all materials to Michelle: qzhang@6jbiotech.com