Research Associate (Surgery)

National University of Singapore; Singapore; On-site; SGD 42,000 - 62,000; Full time

Job summary

The National University of Singapore invites applications for a Research Associate in the Division of Biomedical Informatics under Prof Ngiam Kee Yuan. The role focuses on building advanced AI models, including LLMs and transformer-based architectures, for genomics and multi-omics research.

You will process genomic and transcriptomic data, develop and fine-tune foundation models, and collaborate with researchers and software engineers to create AI tools and publish findings.

Qualifications

• Bachelor’s or Master’s degree in Bioinformatics, Computer Science, Artificial Intelligence, Data Science, or related field.
• Strong programming proficiency in Python and R.
• Experience in bioinformatics including genomic data processing and omics analyses.
• Experience with deep learning and transformer architectures (PyTorch or Hugging Face Transformers).
• Understanding of LLMs and foundation models; training or fine-tuning is a plus.

Responsibilities

• Process and analyze genomic and multi-omics data (GWAS, transcriptomics, functional genomics).
• Research, develop, and train deep learning, transformer-based, and foundation models for biomedical applications.
• Develop and fine-tune LLMs for biological data interpretation and scientific reasoning.
• Integrate multimodal biological datasets for AI model training and evaluation.
• Develop computational pipelines for data processing, model training, and validation.
• Collaborate with researchers and software engineers to create AI applications and prototypes.
• Contribute to research publications, presentations, and grant proposals.

Skills

Bioinformatics

Python

R programming

Deep learning

Transformers

LLMs

Multimodal learning

GPU computing

Education

Bioinformatics/CS/AI degree

Tools

PyTorch

Hugging Face

Job description

Company description

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job description

We are seeking a motivated Research Associate to join the Division of Biomedical Informatics under Prof Ngiam Kee Yuan.

The successful candidate will work on developing advanced AI models, including large language models (LLMs), transformer-based architectures, and foundation models, for applications in genomics, multi-omics, and biomedical research. The role offers opportunities to work with large-scale biomedical datasets, develop innovative AI tools, and contribute to research publications.

Responsibilities

• Process and analyse genomic and multi-omics data, including GWAS, transcriptomics, and functional genomics.
• Research, develop, and train deep learning, transformer-based, and foundation models for biomedical applications.
• Develop and fine-tune LLMs for biological data interpretation and scientific reasoning.
• Integrate multimodal biological datasets for AI model training and evaluation.
• Develop computational pipelines for data processing, model training, and validation.
• Collaborate with researchers and software engineers to develop AI applications and prototypes.
• Contribute to research publications, presentations, and grant proposals.

Qualifications

• Bachelor's or Master's degree in Bioinformatics, Computer Science, Artificial Intelligence, Data Science, or a related field.
• Strong programming proficiency in Python and R.
• Experience in bioinformatics, including genomic data processing, transcriptomics, or other omics analyses.
• Experience with deep learning and transformer architectures including PyTorch or Hugging Face Transformers.
• Understanding of LLMs and foundation models, including model architectures, training, or fine-tuning.
• Experience with foundation model pretraining, self-supervised learning, or multimodal learning is a strong advantage.
• Familiarity with GPU computing, cloud platforms, or high-performance computing is an advantage.
• Strong analytical, problem-solving, and independent research skills.
• Excellent written and verbal communication skills, including scientific writing and presentation.