14 optimization-nonlinear-functions-"Prof" Postdoctoral positions at Purdue University in United States
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read more about us and our science here: https://www.eaps.purdue.edu/bramson . Please direct all questions to Prof. Ali Bramson (BramsonA@purdue.edu). The position is expected to run for 2 years, with
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immediately and is expected to run for 2 years, with opportunities to seek additional funding. Please direct all questions to Prof. Briony Horgan (briony@purdue.edu). Applications must include a CV and a
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energy loss spectroscopy and other applied transmission electron microscopy techniques is preferred. The position is available immediately and is expected to run for 2 years pending availability of funding
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The Quantum Semiconductor Systems Group under the direction of Prof. Michael Manfra seeks a scientist with expertise in semiconductor nanofabrication to support several projects related to the development and
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, collaboration, high-quality work, and real-world problem solving. This position will conduct numerical simulation studies, work on research projects with external partners, mentor and guide graduate student
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spatial transcriptomics, precision medicine and climate data. The initial appointment is for one year, renewable for one additional year subject to satisfactory performance. The postdoctoral fellow will be
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disparities in supportive care medication (SCM) use, using national datasets (e.g., SEER-Medicare, SEER-MHOS), predictive analytics, and stakeholder-engaged methods. The lab is committed to actionable research
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Improvement and Regeneration Center (HTIRC.ORG) in West Lafayette, Indiana. The postdoc will actively work with project personnel from USDA Forest Service, University of Kentucky, Penn State University, Purdue
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spatial transcriptomics, precision medicine and climate data. The initial appointment is for one year, renewable for one additional year subject to satisfactory performance. The postdoctoral fellow will be
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning