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Energy-Water Systems (I- CREWS ), which seeks to increase understanding of how physical infrastructure, data, governance, local knowledge, and community context shape resilience under meteorological
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. Knowledge of forage nutritive value analysis and livestock nutrition metrics. Experience integrating agronomic datasets with animal production or agricultural economic analyses. Familiarity with ARM
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knowledge, close attention to textual evidence and the ability to accommodate several plausible readings. The PhD candidate will develop computational methods and evaluation resources for culturally
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dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and mission responsiveness. Building on this, the fellowship will also explore applications in fragile or complex
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dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has