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Scholar (FP01) – AI Imaging & Retinal Disease who is interested in ophthalmology to assist in refinement of AI models as well as validation of new biomarkers and data analysis to be able to predict whether
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented
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classes and their roles in scientific applications, such as deep neural networks (DNNs), convolutional neural networks (CNNs), transformer models, and graph-based neural networks. Familiarity with software
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universities. A central component of this position is Extension. The faculty member will engage directly with county extension agents, producers, land managers, and agricultural stakeholders to translate
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About the Opportunity The successful candidate will contribute to an ambitious project developing perceptual AI agents that assist humans in daily activities through behavioral understanding and
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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, biophysics, mathematics, or related field 8+ years of experience with agent-based models or physics-based models 5+ years of experience managing a scientific team of 5 or more people 2+ years of experience
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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systems • Healthcare operations, resource allocation, and workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi
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support research in: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics