Scientist - AI/ML/LLM Enhancement of Tools (A*STAR BII)

A*STAR RESEARCH ENTITIES; Pasir Panjang; On-site; MYR 150,000 - 200,000; Full time

Job summary

A leading research organization in Malaysia seeks a skilled Scientist to enhance its genomic platform using AI and ML technologies. The role involves developing prototypes, collaborating with bioinformatics teams, and contributing to innovative solutions in pathogen surveillance. Candidates should have a PhD and experience with machine learning frameworks like PyTorch and TensorFlow. This position offers the chance to translate cutting-edge research into practical applications that improve public health.

Qualifications

• PhD in a relevant field with specialization in AI/ML.
• Hands-on experience with machine learning frameworks.
• Experience with NLP/LLM platforms.

Responsibilities

• Develop and implement AI/ML based enhancements.
• Assist in incorporating LLMs for user functionalities.
• Prototype and evaluate machine learning models.

Skills

Machine Learning

Artificial Intelligence

Data Science

Bioinformatics

Python

Education

PhD in Computer Science, Data Science, Bioinformatics, or related field

Tools

PyTorch

TensorFlow

Scikit learn

Hugging Face Transformers

OpenAI APIs

Job description

We are seeking a highly skilled and motivated Scientist who will support the development and evolution of our genomic platform by integrating cutting edge technologies, including Artificial Intelligence (AI), Machine Learning (ML), Federated Learning (FL), Synthetic Data Generation, and Large Language Models (LLMs). This role works in close collaboration with the visualization, bioinformatics, and data science teams to optimize how users interact with and derive insights from global pathogen surveillance data.

The candidate will play a key part in identifying opportunities for technological integration, developing prototypes, and translating AI/ML research into practical enhancements across tools, trackers, and reports related to emerging and priority pathogens.

Job Responsibilities:

• Develop and implement AI/ML based enhancements for platform tools and trackers, including features for anomaly detection, predictive analytics, and automated data classification.
• Assist in the incorporation of LLMs to support natural language interfaces, automated summaries, and smart query functionalities for users.
• Support the integration of federated learning and synthetic data techniques to improve privacy preserving analytics and model training.
• Collaborate with domain experts to define use cases where AI technologies can augment genomic data visualization, exploration, and reporting.
• Prototype and evaluate machine learning models using real world pathogen data, assessing performance, scalability, and interpretability.
• Contribute to backend pipelines that power interactive dashboards, ensuring AI features are seamlessly integrated and optimized for real time usage.
• Engage with end users to gather feedback on AI driven features and iterate on functionality based on usability insights.
• Document model development, deployment workflows, and system behavior for reproducibility and future scaling.
• Stay on top of emerging AI/ML technologies and trends in genomics, recommending innovations for future adoption.

Job Requirements:

• PhD in Computer Science, Data Science, Bioinformatics, Computational Biology, or a related field with specialization in AI/ML.
• Hands on experience with machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit learn) and NLP/LLM platforms (e.g., Hugging Face Transformers, OpenAI APIs).
• Familiarity with modern AI architectures, including transformers, generative models, and federated learning frameworks.
• Demonstrated experience applying AI/ML to biological or public health datasets is highly desirable.
• Proficiency in Python and working knowledge of APIs, backend services, and data processing pipelines.
• Understanding of bioinformatics data formats and pathogen genome data is a plus.
• Ability to translate technical innovations into practical, user facing features with measurable impact.
• Strong problem solving skills, independence, and a collaborative approach to interdisciplinary work.
• Excellent communication skills for presenting results to technical and non technical audiences.