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Jobfoundry
A*STAR

[50004073-RSE2] Scientist, Computing & Intelligence

A*STAR
ResearchSingaporeFull-time3 weeks ago
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About the role

AI summarised

This is a senior scientist role in computing and intelligence at a healthcare AI research organization. The role focuses on developing novel architectures and training methods for large language models, agentic AI, and multimodal foundation models, with applications in clinical and biomedical domains. Responsibilities include research, translation of AI systems to healthcare, and scientific leadership through publications and funding.

ResearchFull-time

Key Responsibilities

  • Develop novel architectures, training strategies, and optimization methods for LLMs, agentic AI, vision foundation model and multimodal foundation models.
  • Advance instruction tuning, reinforcement learning (RLHF/GRPO), retrieval-augmented generation (RAG), and knowledge-grounded reasoning in medical AI.
  • Design and implement multimodal learning pipelines that integrate text, imaging, omics, and real-world clinical data.
  • Prototype AI systems for clinical and biomedical applications (e.g., decision support, conversational AI, population health, drug discovery).
  • Benchmark models against state-of-the-art healthcare AI datasets and evaluation frameworks.
  • Collaborate with industry and healthcare partners to enable translation, licensing, and commercialization.
  • Publish in top-tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL) and high-impact biomedical journals (e.g., Nature Medicine).
  • Contribute to open science initiatives (datasets, model releases, benchmarks).
  • Secure funding through collaborative research proposals with academia, healthcare institutions, and industry.

Requirements

  • Minimum Qualifications
  • PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
  • Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, ACL) or high-impact biomedical journals.
  • Deep expertise in LLMs, vision foundation models, or multimodal AI.
  • Strong skills in deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed/HPC training.
  • Preferred Qualifications
  • Experience in large-scale LLM and/or foundation model training and deployment.
  • Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics).