AI Scientist, Generative AI Models for the Creation of RNA-Based Vaccines (GIS)

AI Scientist, Generative AI Models for the Creation of RNA-Based Vaccines (GIS)

Agency for Science, Technology and Research – Queenstown

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of AI in Genomics, led by Prof. Mile Sikic, which uses advanced bioinformatics and deep learning approaches to develop next-generation models for genomic data analysis. We are group a of computer scientist with a mission to improve healthcare using advance deep learning models. Located in the heart of Singapore's thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore's vibrant research ecosystem and strong support for innovation.

Project background

Messenger RNA (mRNA)-based therapeutics, including vaccines, represent a transformative class of drugs for infectious diseases and cancer immunotherapy. Their programmable nature allows rapid adaptation to evolving pathogens and personalized medicine, but effective design of mRNA molecules remains a key bottleneck. Current development relies on trial-and-error methods, leading to long timelines, high costs, and suboptimal outcomes.

This project aims to develop an agent-based generative AI system to design both linear and circular mRNA molecules. By unifying the design process into a data-driven, adaptive pipeline, the system will optimize vaccine stability, minimize unwanted immune responses, and accelerate early-stage research and development from months to hours. The outcome will be a robust, scalable platform for creating effective mRNA vaccines for infectious diseases, cancer, and beyond.

We are looking for a highly motivated postdoctoral researcher to :

• Run large-scale pretraining on high-performance computing infrastructure
• Perform model finetuning and hyperparameter optimization
• Evaluate models on experimental data

Profile

We welcome applications from candidates with :

We offer

The position is initially offered for one year, with the possibility of renewal.

How to apply

We look forward to receiving your application with the following documents :

We accept applications submitted through our online application portal or via email directed to Prof. Sikic at

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