A Research Assistant position is available in the laboratory of Prof. Shan Wang (person.zju.edu.cn/shanwang#0) at Zhejiang University. We are seeking a highly motivated individual to join an interdisciplinary project at the intersection of stem cell biology, high-content screening, and artificial intelligence.
Research Direction
Stem cell-based therapies hold great promise for treating a wide range of complex diseases, including chronic disorders, metabolic diseases, and age-related pathologies. High-content screening (HCS) has emerged as a powerful platform for future drug discovery, enabling rapid, high-throughput, and high-resolution fluorescence imaging to capture drug-induced effects on cell morphology, proliferation, differentiation, and apoptosis at the single-cell level.
Our laboratory integrates cutting-edge technologies to develop next-generation drug discovery platforms. We combine:
• High-content screening data
• Protein–small molecule interaction information
• Multi-omics datasets
• Deep learning algorithms (e.g., convolutional neural networks)
Our goal is to build AI-driven generative models for precision drug design, with a focus on targeting disease-associated stem cells.
Position: Bioinformatics Research Assistant
The successful candidate will apply machine learning and deep learning algorithms to advance drug discovery platforms.
Responsibilities:
• Develop models to predict drug toxicity based on high-content imaging data
• Build drug screening models using protein–small molecule interaction information
• Construct gene regulatory networks using multi-omics sequencing data
• Collaborate with interdisciplinary team members on generative AI model development
• Master’s degree or higher in Bioinformatics, Pharmaceutical Sciences, Computer Science, or a related field
• Familiarity with mainstream deep learning and machine learning algorithms (e.g., CNN, RNN, GCN, RF, SVM)
• Proficiency in programming languages such as Python, Java, Kotlin, SQL, or Shell
• Experience with common deep learning, machine learning, and cheminformatics libraries (e.g., PyTorch, TensorFlow, scikit-learn, RDKit, DeepChem, dgllife)
• Prior experience in building drug prediction models using AI algorithms is preferred
Please send your CV, a brief statement of research interests, and contact information for two references to:
Prof. Shan Wang
shan_wang@zju.edu.cn