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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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a key role in building and integrating of AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives), and integrating a multimodal detection
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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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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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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks
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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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, 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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(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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cloud hosted AI platforms providing various emerging capabilities to all university members, such as AI chat bots, AI agents, etc. This includes configuring access policies, monitoring resources
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cues play a role analogous to conditioned stimuli: they are signals that, once learned, allow the agent to anticipate the consequences of its actions. Scientific Motivation: Learning-based navigation