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, and publication of major results from the experiment. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS C
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
or polar oceanography. Experience with high-performance computing, GPU-accelerated models (e.g., Oceananigans.jl), or advanced flow measurement techniques (e.g., PIV, LIF). Interest in mentoring graduate
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Qualifications • Ph.D. in Chemical Engineering, Materials Science, Chemistry, or related field • Experience with computational modeling and simulation of polymers • Record of first-author publications Preferred
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substantial knowledge of state-of-the-art principles and theories. 5. Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions. 6. Adheres
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory invites applications for a postdoctoral researcher position in the field of hybrid quantum computing. This exciting project
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neurotechnologies for translational medicine. The lab specializes in computational modeling, physiological signal analysis, and innovative neuromodulation strategies for neurological disorders such as epilepsy
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appointment, renewable for two additional years pending productivity, performance, and overall fit. The postdoctoral program enables associates to build a high caliber scholarly portfolio in social-structural
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computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient
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Associate to join our lymphoma research program. The successful candidate will work at the interface of cancer biology, functional genomics, and translational research, with a focus on understanding the
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, investigating (a) cumulative environmental impacts, (b) the use of census microdata for social vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda