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background in individual- /agent-based modelling Experience with modelling of animal energetics Strong R and Netlogo skills Good understanding of movement & population ecology Experience in publishing
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. • Familiarity with MODFLOW, MATPOWER, OpenDSS, Machine Learning based emulators, or agent-based modeling. • Knowledge of scenario development, resilience frameworks, and socio-environmental-technological systems
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documentation (reports and specification notes).; - Develop simulation models (e.g., agent-based/spatial) of animal movement and pasture dynamics, calibrated from real data.; - Integrate ML forecasts (meteorology
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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programming will be advantageous. Knowledge of intelligent decision agents based on graph neural network or similar will an advantage. Key Competencies Good knowledge in reliability analysis. Experience in
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with agent-based models, statistical methods, artificial intelligence, process modeling, and data visualization Experience working in teams with people from various socioeconomic, cultural, and
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infrastructure systems such as power, water, sewer, and communications systems. It introduces existing physics-based modeling of these systems. It then covers the main tools used to simulate, optimize, and analyze
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candidates may include: 1.Energy modelers with expertise in integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics
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) and an agent-based reinforcement learning system can developed to identify and optimise safe journeys to reach affected forest plantations. The specific research objectives will be co-developed with
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to identify user needs and requirements for efficient, scalable and reliable data pipelines and models that support data-driven initiatives. Support automation of operational workflows using Agentic AI