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InnoHK Centre for Translational Stem Cell Biology (InnoHK CTSCB) leads global innovation in regenerative medicine, driving next-generation stem cell technology to achieve real-world impact. Through partnerships with the University of Hong Kong and the University of Cambridge and supported by the InnoHK initiative of the Innovation and Technology Commission, we transform pioneering discoveries into innovative applications and commercial successes.

Our patented Expanded Potential Stem Cell (EPSC) technology uniquely enables the generation of every human cell type, including embryonic and extra-embryonic lineages. This breakthrough technology accelerates the development of intelligent drug screening, precision medicine, and cell-based therapies, ultimately improving patient outcomes and enhancing quality of life worldwide.

Driven by our vision for healthy longevity and a spirit of collaboration, InnoHK CTSCB brings together leading experts from around the world, fostering a vibrant culture of innovation. Our research is strategically organized into three interconnected programmes that address pressing medical needs. 

This position centers on developing state‑of‑the‑art AI models to predict cellular responses to drug perturbations. The successful candidate will help build a commercially oriented high‑throughput drug screening platform and advance machine learning methods for drug discovery and therapeutic applications using large‑scale chemically induced perturbation datasets.

• Develop deep learning models to predict transcriptomic drug perturbations using transcriptome perturbation databases.
• Construct gene regulatory networks (GRNs) leveraging perturbation datasets.
• Contribute to research related to Virtual Cell modeling.
• Prepare technical reports and model documentation.
• Participate in other research tasks assigned by the team.

• Ph.D. in Computer Science, Data Science, Bio/Cheminformatics, Computational Biology, or a related field.
• Strong proficiency in Python for scientific computing and deep learning (e.g., PyTorch).
• Project experience with diffusion models, Generative AI, or Transformer architectures.
• Publication record in influential journals or conferences in relevant fields.
• High motivation, strong communication skills, and a passion for solving complex scientific problems.
• Experience with cellular perturbation modeling and/or virtual drug screening.
• Project experience in biological sequence modeling (DNA, RNA, peptides).
• Research experience in genomics, drug discovery, or single‑cell analysis.
• Familiarity with cheminformatics tools (e.g., RDKit).

Please email the following materials to recruit@hkstemcell.hk
Email subject: Application — Machine Learning Engineer — [Your Name]

1. Curriculum Vitae (CV)
2. Earliest available start date

Qualified applicants will be contacted for interview on a rolling basis.