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Research Assistant - Neuro-Symbolic Reasoning

$86k to $117k

Clayton campus, CampusPart-timePosted Oct 1, 2026

Job description

Research Assistant

  • Neuro-Symbolic Reasoning Job No.: 697933 Location: Clayton campus Employment Type: Part-time, fraction (0.5) Duration: 6 month fixed-term appointment Remuneration: Pro-rata of $86,195 - $116,981 pa Level A (plus 17% employer superannuation) Amplify your impact as a Research Assistant at a world top 50 University Join our inclusive, collaborative community advancing trustworthy AI Be surrounded by extraordinary ideas - and the people who discover them The Opportunity 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. We are seeking someone with a PhD or near completion in Artificial Intelligence, Computer Science, Machine Learning or a closely related discipline, together with 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 Py. Torch, JAX or Tensor. Flow, combined with excellent analytical, problem-solving, communication, organisational and project management skills, will also support success in this role. Join a collaborative research environment developing explainable and trustworthy AI systems for collaborative decision-making and apply for this exciting Research Fellow opportunity. About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing to something ground breaking – a place where great things happen. We value difference and diversity , and welcome and celebrate everyone's contributions, lived experience and expertise. That’s why we champion an inclusive and respectful workplace culture where everyone is supported to succeed. Some 20,000 staff work for Monash around the world. We have 95,000 students, four Australian campuses, and campuses in Malaysia and Indonesia. We also have a major presence in India and China, and a significant centre and research foundation in Italy. In our short history, we have skyrocketed through global university rankings and established ourselves consistently among the world's best tertiary institutions. We rank in the world’s top-50 universities in rankings including the QS World University Rankings 2026. Together with our commitment to academic freedom , you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities. Learn more about Monash . Today, we have the momentum to create the future we need for generations to come. Accelerate your change here. Monash supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments. This includes supporting parents . To Apply For instructions on how to apply, please refer to ' How to apply for Monash Jobs '. Your application must address the Key Selection Criteria. Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups. Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University. Enquiries: Dr. Naim Rastgoo, Senior Research Fellow, Department of Data Science and Artificial Intelligence, naim.rastgoo@monash.edu Position Description: Research Assistant Applications Close: Thursday 29th October 2026, 11:55pm AEDT

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