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About the Opportunity The successful candidate will contribute to an ambitious project developing perceptual AI agents that assist humans in daily activities through behavioral understanding and
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therapeutic agents, using cell-based models as well as patient-derived xenograft models of liver cancer. This position is suitable for a highly motivated self-starter who excels in a dynamic environment
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are designed to empower (forms of) safeguarded AI specifically with LLMs and T2Is, by O1) mapping PRLs automatically onto representations usable by autonomous agents to engage in debate; O2) using
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based
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methods (for example, learning-based, network-based, or agent-based approaches) to analyse dynamic decision behaviour, rather than focusing solely on predictive or optimisation performance prepare and
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modules to farmer’s, cooperatives, extension agents, etc. Data scheduling, collection, analysis, interpretation, and presentation. Supervise Postdoc, PhD and Master students as well as interns Project
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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting Models Basic Qualifications A Ph.D. or equivalent degree
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, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
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Motion Planning in harsh and dynamic GPS-denied environments - Autonomous inspection planning with persistent semantic scene abstraction for advanced reasoning and task planning - Multi-agent collaborative
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agents · Base Salary, Level A Step 6 $113,400 p.a. + 17% superannuation About the opportunity The School of Chemistry is one of Australia's main centres for chemical research and education. We have