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technologies, including drones, robotics, and self-driven laboratories. The appointees will engage in research on the development of intelligent hybrid power architectures to support autonomous operation in
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docking to investigate viral spike/capsid architecture, thermal stability, and immune epitope accessibility. AI/Deep Learning: ML/DL model development (e.g., PyTorch, Lightning) for predicting antigenicity
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, RoseTTAFold, ESMFold), molecular dynamics (MD) simulations, or protein-protein/antigen-antibody docking to investigate viral spike/capsid architecture, thermal stability, and immune epitope accessibility. AI
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