Biomedical ofertas em United States

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

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.

• 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.