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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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the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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communications (ISaC) to network design using O-RAN; from statistical learning theory to software defined radio (e.g., USRP) prototypes. The Bradley Department of Electrical and Computer Engineering has both
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from proximity to healthcare startups, biotechnology firms, and a thriving biomedical community, allowing for networking and translational research opportunities. The lab has further strong collaboration
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. Understanding of high-order methods for fluid flows. Understanding of turbulence, boundary layer flows, multi-phase flows, chemical kinetics, combustion, and detonations. Experience in mesh generation with
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to study genetically defined neuron types involved in perceptual function and dysfunction in behaving rodents. Our new GEVIs and imaging approaches (see Kannan, Vasan et al., Nature Methods , 2018; Science
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university-wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus on cancer treatment and research, neuroscience, advanced biotechnology and medicine
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. The appointment is for one year, renewable for a second year given the availability of funds. The focus is on fundamental properties of simulated neural networks, like neural scaling laws, as they manifest in
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neural networks, like neural scaling laws, as they manifest in metrics specific to robotics and impact robotics applications. The thrust of the research is multidisciplinary. The successful candidate will