Research Assistant - Neuro-Symbolic Reasoning

Monash•Clayton, NC

6d•$86,195 - $116,981•Hybrid

About The Position

Join a research program advancing trustworthy AI collaboration through the development of novel neuro-symbolic AI methods for reasoning over multi-agent interactions. This Research Assistant position will contribute to research exploring how temporal knowledge representation, abductive and probabilistic reasoning and machine learning can be used to understand complex behaviours such as reliability, competence, transparency and trust. The position will design and develop innovative reasoning algorithms and knowledge-based, probabilistic and neuro-symbolic frameworks integrated with machine learning and reinforcement learning. The role will contribute to high-impact research publications, research software, experimental frameworks and evaluation methodologies.

Requirements

PhD or near completion in Artificial Intelligence, Computer Science, Machine Learning or a closely related discipline.
Strong research expertise in areas such as neuro-symbolic AI, knowledge representation and reasoning, temporal reasoning, probabilistic or differentiable logic, graph-based machine learning, knowledge graphs or multi-agent reinforcement learning.
Strong programming skills in Python and AI frameworks such as PyTorch, JAX or TensorFlow.
Excellent analytical, problem-solving, communication, organisational and project management skills.

Responsibilities

Design and develop innovative reasoning algorithms and knowledge-based, probabilistic and neuro-symbolic frameworks integrated with machine learning and reinforcement learning.
Contribute to high-impact research publications, research software, experimental frameworks and evaluation methodologies.