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infrastructure, including Docker-based microservices, large language model (LLM) inference servers on GPU clusters, vector database and retrieval-augmented generation (RAG) pipelines, and observability stacks
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databases to assess ecosystem response to environmental forcing. The primary research focus is AI-forward, experiment-driven. This position encourages leveraging AI/ML methods to assess plant physiological
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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