ATMRI at NTU a highly motivated Research Fellow to join its dynamic research team working at the forefront of Artificial Intelligence (AI), Multi-Agent Systems (MAS), Collaborative Decision Making with a strong focus on real-world applications of reinforcement learning. The role involves conducting cutting-edge research in AI targeting high impact research publication in top tier AI conferences and journals.

You will be expected to:

• Conduct cutting-edge research in:
  Multi-Agent Systems (MAS) for complex, dynamic, and uncertain environments.
  Multi-Agent Reinforcement Learning (MARL), including cooperative, competitive, and mixed settings.
  Collaborative decision-making frameworks and decentralized learning algorithms.
  Adaptive, meta-learning, and context-aware strategies to enhance policy generalization across tasks.
  Hierarchical and modular agent architectures to enable scalable coordination.
• Design and implement simulation environments, integrating real-world data and domain-specific constraints, for model training and validation.
• Perform visual analysis to visualize agent behaviors, emergent strategies, and system-level outcomes.
• Contribute to:
  High-impact publications in top-tier AI conference and journals.
  Internal knowledge transfer, and collaborative research efforts.
• Develop and evaluate AI models, including, but not limited to, those for Multi-Agent Systems, Multi-Agent Reinforcement Learning, and Collaborative Decision-Making frameworks.
• Design and implement simulation platforms and experimental pipelines for algorithm validation and visualize simulation and experimental results to support decision-making and research findings.

Qualifications & Competencies:

• Minimally a PhD degree in Artificial Intelligence, Computer Science, Optimization, or a related field.
• Strong foundation in multi-agent systems, MARL, Game Theory.
• Strong background in Mathematics and modelling.
• Good English writing and communication skills for research work.
• Proficiency in Python, experience with PyTorch, NumPy, and relevant data science and machine learning tools.
• Able to work independently and comfortably with a team and external/international collaborators.
• Able to handle multiple tasks relevant to both project and research.
• Experience in publication in top-tier AI conferences/journals is desired.
• Experience in prototypes and intelligent tools development is desired.

We regret to inform that only shortlisted candidates will be notified.