药明康德新药欢迎最新从事过自然语言处理等行业的优秀人才加入我们,上海药明康德新药开发有限公司将为您提供广阔的发展平台!
工作职责:
1. Develop and optimize machine learning (ML) algorithms including major Deep Learning models, e.g. graph neural networks (GNN), NLP DL attention models (Seq2seq, transformers, etc.) to solve realistic chemistry AI problems in synthesis planning
2. Integrate domain knowledge and cheminformatics technologies (RDKit, ChemDraw, MarvinJS etc.) into ML to address real challenges in medicinal chemistry areas
3. Digest up-to-date state-of-the-art (SOTA) ML algorithms, and develop systematic experiment pipelines to evaluate and reproduce SOTA results
4. Generate technical documentation, help and drive junior project members to deliver expected technical results
5. Work with other teams and departments to transfer ML prototypes into systems and platforms
任职资格:
1、***/*** (or equivalent overseas) graduates; Master degree/PhD degree in computer science
2、Requirement: Associate Director: 3-year+ experience in AI/ML, Director: 4-year+ in AI/ML with Chem AI hands-on experience; Senior Director: 5-year+ in AI/ML plus track records in AI and Chem AI research & devlopment
3、Master/PhD in STEM or related areas (computer science/engineering preferred) with strong hands-on technical and industrial experience in ML and AI projects; expertise in graph neural networks and NLP deep learning models is preferred
4、Excellent problem formulation and problem solving skills with outstanding communication and teamwork capability, good sense of data and outstanding research capability;
5、Outstanding programming skills using Python (additional experience in SQL/Java/C/C++ is a plut);
6、Strong hands-on technical skills in implementing Deep Learning (DL) algorithms such as graph neural networks (GNN),RNN, RSTM, Transformer with DL frameworks (Tensorflow/Pytorch), experience in developing customized algorithms to improve outcomes in realistic applications
7、Strong research capability in digesting and reproducing up-to-date ML/AI algorithms and results
8、Knowledge and experience in pharmaceutical and clinical domains is preferred; experience in reaction, retrosynthesis and other chemical space related ML applications is a strong plus
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