Research Fellow (Machine Learning)

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

Une université leader en recherche recherche un Research Fellow dynamique pour rejoindre son équipe spécialisée en Intelligence Artificielle. Ce poste implique de mener des recherches sur des systèmes multi-agents, de développer des modèles d'IA, et d'obtenir des publications dans des conférences de haut niveau. Un idéal candidat aura un docteur en IA ou un domaine connexe et une forte base en mathématiques.

Qualifications

• PhD en IA or related field requis.
• Forte compétence en systèmes multi-agents et MARL.
• Proficient en Python et outils de science des données.

Responsibilities

• Mener des recherches sur les systèmes multi-agents et le renforcement.
• Développer et évaluer des modèles d'IA.
• Contribuer aux publications de recherche de haut niveau.

Skills

Multi-Agent Systems

Multi-Agent Reinforcement Learning

Game Theory

Mathematics

Python

PyTorch

NumPy

Education

PhD in Artificial Intelligence, Computer Science, Optimization

Tools

Data Science Tools

Machine Learning Tools

Job description

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.