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Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models and multi-agent systems for conservation genomics; perform feature engineering using chromosome-level genome assemblies. 15
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developers of Jarvis . Anticipated Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models and multi-agent systems for conservation genomics; perform feature engineering using
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, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
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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
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scaling cloud-based activity-based mobility analytics systems (AWS/Azure/GCP) for large multi-city datasets Enhancing and deploying computational platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc