Principal Scientist, Computing & Intelligence, IAIC

Job Overview

The Institute of Advanced Intelligence and Computing (IAIC) under A*STAR is seeking a motivated Principal Scientist to lead pioneering research in Healthcare AI Safety, Trustworthy AI practices, and Responsible AI Systems. The role focuses on creating methods, frameworks, and technologies that guarantee the safety, reliability, transparency, and clinical trustworthiness of AI implementations within healthcare environments.

Core Responsibilities

• Perform innovative research in Healthcare AI Safety, Trustworthy AI, Machine Learning, and Artificial Intelligence.
• Create new methodologies related to AI Safety and Alignment, Trustworthy/Responsible AI, Explainable AI, AI Evaluation and Benchmarking, Robustness, Human-AI Collaboration, AI Governance, and Risk Management.
• Design strategies to identify and manage AI failures, biases, hallucinations, and unsafe conduct.
• Develop uncertainty quantification tools, confidence assessments, and frameworks supporting risk-aware decisions.
• Formulate safety protocols for foundation models, large language models, multimodal AI, and agent-based AI systems applied to healthcare.
• Establish evaluation standards for clinical safety, fairness, reliability, and generalizability across diverse patient groups and medical settings.
• Create monitoring systems for post-deployment supervision, drift detection, and ongoing safety evaluations.
• Develop mechanisms enabling human oversight, escalation procedures, and safe collaboration between clinicians and AI within workflows.
• Advance evaluation schemes for clinical decision support tools, healthcare copilots, and autonomous healthcare agents.
• Enhance approaches that protect patient privacy, secure data, and promote responsible healthcare data usage.
• Collaborate with clinical and regulatory stakeholders to facilitate safe AI integration in healthcare.
• Contribute to the creation and adoption of AI governance frameworks, safety standards, and regulatory practices.
• Translate theoretical AI safety advances into practical tools, platforms, and operation models for healthcare providers.
• Support technology transfer, intellectual property creation, and commercialization efforts.
• Lead publication efforts in top-tier AI, machine learning, healthcare, and AI safety forums.
• Participate in grant writing, project planning, and strategic research development.
• Mentor junior researchers and engineers while representing IAIC in partnerships with medical institutions, authorities, and industry.

Candidate Requirements

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Biomedical Informatics, Healthcare Informatics, or related fields.
• Demonstrated excellence in AI/ML research with publications, patents, or impactful projects.
• Proficient Python programming skills along with experience in machine learning libraries like PyTorch or TensorFlow.
• Hands-on experience developing and assessing machine learning and deep learning architectures.
• Strong passion for AI safety, responsible AI, trustworthy systems, and healthcare-focused AI applications.

Preferred Qualifications

• Expertise or experience with AI Safety and Alignment, Trustworthy and Responsible AI, Explainable AI (XAI), Foundation and Large Language Models.
• Knowledge of Agentic AI systems, Healthcare AI, Clinical Decision Support, AI Evaluation, and Benchmarking.
• Understanding of Human Factors, Human-AI interaction, Regulatory Science, AI Governance, Healthcare Data Privacy, and Security.

Work Environment and Benefits

• Influence the advancement of safe, trustworthy, and responsible AI technologies in healthcare.
• Access to cutting-edge computational resources, healthcare datasets, and research infrastructure.
• Collaborate with top AI scientists, clinicians, healthcare providers, regulators, and private sector partners.
• Engage in both foundational research and practical AI deployment initiatives.
• Participate in shaping national and international AI safety guidelines and frameworks for healthcare.