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Field
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sparse-regression based techniques to derive interpretable and computationally efficient differential equation models from computationally intensive multi-cellular agent based models (ABMs) of Epstein–Barr
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), - land use planning, social vulnerabilities, and economic issues (inequalities, accessibility, human development). This research and its contribution to public policy are based on methods and techniques
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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potato diseases, alter the plant microbiome and host biocontrol agents) and productivity (yield); understand the communication needs of potato farmers; and to co-create evidence-based communication
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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial
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-agent AI, cooperative vision, and compression protocols so fleets of intelligent machines can perceive the world—robustly, efficiently, and in a trustworthy manner—even when individual sensors fail
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are to assess the impact of cover crops on potato health (including their potential to reduce potato diseases, alter the plant microbiome and host biocontrol agents) and productivity (yield); understand
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Lab The EMERGE lab at NYU is seeking to hire a postdoc to work on scaling and deploying end-to-end RL planning agents for autonomous vehicles. Based on prior work on creating high performing self-play
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the crisis of multilateralism and debates on organisational culture, principal-agent relationships, and micro-level responses to macro-level ambiguity. Where you will work The mission of the Faculty
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language processing (NLP), and fine-tuning techniques Familiarity with structured reasoning, chain-of-thought processes, and agent-based systems is beneficial Strong programming skills (preferably Python); experience