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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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microbiomes to optimize end-of-life material processing and circular resource recovery. This position will be part of the UT-ORII’s Circular Bioeconomy Systems (CBS) Convergent Research Initiative (CRI
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DIPF | Leibniz Institute for Research and Information in Education contributes to addressing challenges in education through empirical research, digital infrastructure and knowledge transfer. At its
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through preclinical models to clinical trials within Duke and collaborating institutions We seek postdoctoral fellows with experience or knowledge in cellular immunotherapy, in vitro/in vivo imaging, and
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rich contextual measures of psychosocial environments, SISU and PRISM characterize families and schools optimal for psychological development in a global crisis. Our explanatory variables of interest
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and simulation tool that will be developed in this project. Previous knowledge and experience in some of all of the following are desired and advantageous: high-level simulation tools (such as Gem5
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method development & optimization: Proven ability to develop, optimize, and validate LC-MS/MS methods for complex sample types. Expertise in extracting proteins, metabolites, and lipids and performing nano
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in Python and R for data analysis, modeling, and visualization. Proficiency in building efficient pipelines that use optimized software to process large datasets. Proficiency in supervised
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journals, presenting at conferences, and engaging in knowledge translation activities. Support faculty and trainees in disseminating impactful research that advances emergency medicine practice
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machines are programmed for material removal. Considerable expert knowledge is required for the necessary selection of suitable production tools and the definition of tool movements. The increasing