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using diverse data sources, including field-collected biological samples, on-farm sensor data, artificial intelligenceāderived outputs, and video-based analytics, to support disease surveillance and
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Requirements Required experience includes: Significant experience implementing high performance sensor fusion and state estimation algorithms in real systems using, e.g., Kalman filters, particle filters, etc
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. System & Simulation Integration: Integrate legacy utility documentation, real-time sensor streams, and domain-specific engineering/mechanics modeling tools into a unified AI-driven digital twin testbed
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