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North America, to improve an existing model for the spread of Cyvirus cyprinidallo3 (also known as Cyprinid Herpes Virus or CyHV-3) as a biocontrol agent for common carp in Australia. The modelling will
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North America, to improve an existing model for the spread of Cyvirus cyprinidallo3 (also known as Cyprinid Herpes Virus or CyHV-3) as a biocontrol agent for common carp in Australia. The modelling will
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of oncologic agents under development, providing unique insights into the patient experience of symptomatic adverse events that traditional clinical assessments may miss. Our published proof-of-concept study
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models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search-based methods to achieve personalised and novel outputs. This position will have a
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security models and proofs, working prototypes, and clear evaluation methods that can translate into auditable, standards-aligned controls for high-assurance identity use cases. You will work with a cross
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translational questions, including but not limited to drug efficacy and safety prediction, mechanism-of-action inference, biomarker discovery, causal or network-based modeling of biological systems, and drug
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research projects in computer vision, machine learning, AI, and robotics. Projects may include physically-grounded AI guidance agents, modeling of multimodal data, and generative AI systems for situated
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including multiple and embodied AI agents. Countering the current trends of very large models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search
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interdisciplinary pipelines to identify effective RNA drugs against human diseases: AI-driven RNA discovery – using AI agents to prioritize the therapeutic potential of human lncRNAs (supported by the NHLBI
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recently developed mathematical theory, linking stochastic, network, and agent-based modelling, describing how this emergent behaviour supports essential maintenance and sharing of contents through