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Field
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in the cleanroom at the Center for Nanoscale Materials. The candidate will work in a collaborative environment including a network of leading researchers. Position Requirements Recent or soon-to-be
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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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career development plan. The program integrates international, interdisciplinary, and intersectoral elements to provide a well-rounded educational experience. Networking Opportunities: Build lasting
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prospective and current postdocs; build a community for all UNLV postdocs; and provide professional development programs and networking events for postdocs. UNLV currently employs postdoctoral scholars across a
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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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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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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Networks, Systems and Control, Signal processing and Biomedical engineering, and Electric Power Engineering. We work with sustainable and smart solutions to societal challenges, such as energy efficiency and
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network excitability following traumatic brain injury using a variety of techniques, including in vivo whole-cell recording and two-photon microscopy, brain slice physiology, and genetic manipulation
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(BCDI), Laue microdiffraction, ptychographic laminography, and X-ray photon correlation spectroscopy (XPCS) to study strain, dislocation networks, voids, and interfacial morphology. Develop in-situ and