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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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. Training LLMs, large-scale deep learning systems, and/or large foundation models using GPU/TPU parallelization while setting up the environment/system network under various constraints, such as limited
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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-based and network analytic approaches, such as visibility graph analysis, to uncover latent patterns, detect anomalies, and characterize dynamical behavior. This position offers an exciting opportunity
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) are looking to hire a post-doctoral associate to carry out joint research in resilience of neural networks, including large language models (LLMs) and other generative AI systems and foundation models
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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interface their research with the department's existing strengths in communications/signal processing, wireless networks, RF/microwave/THz engineering, IoT, AI, cybersecurity, and computer engineering. The
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external research funding and who can interface their research with the department's existing strengths in communications/signal processing, wireless networks, RF/microwave/THz engineering, IoT, AI
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demonstrate potential for securing external research funding and who can interface their research with the department's existing strengths in communications/signal processing, wireless networks, RF/microwave
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external research funding and who can interface their research with the department's existing strengths in communications/signal processing, wireless networks, RF/microwave/THz engineering, IoT, AI