Job Description

We are looking for AI talent at both Scientist and Engineer levels to join us. Whether you are a PhD-trained scientist pushing the frontiers of research, or an engineer with strong applied AI skills ready to build large-scale systems, you will contribute to innovations that make real impact in healthcare.

Key Responsibilities:

Research & Development



Develop novel architectures, training strategies, and optimization methods for LLMs 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.



Translation & Collaboration



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.



Scientific Leadership



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.

Job Requirements:

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, foundation models, or multimodal AI.

Strong skills in deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed/HPC training.

Experience in large-scale LLM and foundation model training and deployment.

Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics).

Familiarity with biomedical ontologies and knowledge graphs (UMLS, SNOMED CT, PubMed).

Understanding of AI ethics, safety, and regulatory considerations in healthcare.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Type of Employment :

Full-Time

Minimum Experience :

1 Year

Work Location :

Fusionopolis