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systems (Mojo, Julia, Rust, Python), and HPC system co‑design. This position is embedded within the larger DOE ASCR ecosystem, with direct relevance to ongoing efforts, and related AI‑for‑HPC thrusts
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neuromorphic platforms. FPGA / Hardware-Embedded AI: Deployment of SNNs to FPGA-based neuromorphic hardware (e.g., NeuroSpike/NeuroSpark). RTL generation using HLS workflows and evaluation of resource usage
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from plant genomics to phenomics with biological mechanisms embedded in deep neutral networks. GPTgp will allow task-specific training and transfer learning across reactions, pathways, biodesigns, and
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, dimensionality reduction, embeddings, etc.). Understanding of computational scaling techniques for machine learning and high-performance computing. Preferred Qualifications: Expertise in foundational models and