Job Description

We are seeking a passionate and skilled Research Assistant / Research Associate to join the NUS Division of Biomedical Informatics under Prof Ngiam Kee Yuan. You will work at the intersection of healthcare and artificial intelligence, developing transformer-based models and large language models (LLMs) to support applications in clinical decision-making, medical imaging, and drug discovery.

This role offers the opportunity to work with rich, real-world healthcare data, including electronic health records (EHR) and medical images, to build AI tools with direct translational impact in the local healthcare system.

Responsibilities:

• Conduct research, design, and training of transformer-based and deep learning models for healthcare and biomedical applications.
• Develop AI systems that integrate and analyze multimodal data, including electronic health records (EHRs), medical imaging, genomics, and clinical notes.
• Contribute to drug discovery and development efforts using generative models, knowledge graphs, and advanced machine learning techniques.
• Deploy machine learning models in hybrid cloud environments (on-premise and cloud) for both research and operational use.
• Collaborate closely with software engineers and data scientists to build, test, and refine AI applications and prototypes.
• Document model development processes, validation results, and deployment pipelines comprehensively to ensure reproducibility and transparency.
• Assist in the preparation of research manuscripts, technical reports, grant proposals, and academic presentations.
• Support and facilitate teaching activities related to biomedical informatics, AI in healthcare, and related educational initiatives, including lectures, workshops, and mentorship.

Qualifications

• Master’s degree in Bioinformatics, Computer Science, Biomedical Informatics, Statistics, or a related field. Exceptional candidates with a Bachelor’s degree and strong relevant experience will also be considered.
• Demonstrated hands-on experience in deep learning, particularly in domains such as natural language processing (NLP), medical imaging, or drug discovery.
• Strong proficiency in Python, with experience using machine learning frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn.
• Experience with large language model (LLM) fine-tuning, transformer-based architectures, or multimodal learning is a significant advantage.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud Platform, Microsoft Azure) and the deployment of machine learning pipelines in hybrid or cloud environments.
• Prior experience working with healthcare data, including structured electronic health records (EHRs), clinical notes, or medical imaging, is highly desirable.
• Excellent analytical, problem-solving, and communication skills, with a strong emphasis on clear documentation and reproducibility.
• Proven ability to work both independently and collaboratively within multidisciplinary research or engineering teams.

More Information

Location: Kent Ridge Campus

Organization: Yong Loo Lin School of Medicine

Department : Surgery

Employee Referral Eligible: No

Job requisition ID : 29803