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Field
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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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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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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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realize fully capable mobile agents and collaborative autonomous agents. RISC is an integral member of the Center for AI and Robotics (CAIR). CAIR has significant work in localization for autonomous agents
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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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- Exploring Foundational Models and Agentic AI to address challenges in energy storage and conversion. Position Requirements Candidates must meet the following qualifications: 1. Educational Background: - A
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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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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
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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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-in, and performance or creativity degradation in socio-technical decision processes design and implement quantitative methods (for example, learning-based, network-based, or agent-based approaches