12 embedded-systems-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at Iowa State University
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One year of experience working with persons with Parkinson’s disease Department Unit/Website: https://kin.hs.iastate.edu/ Candidates must be legally authorized to work in the U.S. on an ongoing basis
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research projects focused on optimization, data analytics, and control of power distribution systems. This position offers the opportunity to collaborate closely with utility company partners and
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, interfaces, and heterostructures, with particular interest in the superconducting order parameter, thermal and induced quasiparticles, two-level systems, the effects of controlled disorder and emergent
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maize pangenomics and population diversity, with opportunities to contribute to similar analyses in other crop systems, including cotton. Required Minimum Qualifications: PhD in Plant Biology
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model systems. The individual will also contribute to the evaluation of novel vaccine platforms by assessing their safety, immunogenicity, and protective efficacy against viral pathogens. In addition to
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: Molecular Biology, Genomics, Genetics, or equivalent. Experience working in plant model systems A demonstrated track record of publishing independent research, including at least one first-author peer
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goal is to identify which physical mechanisms – surface and interface spins, magnetic defects, two-level systems, trapped flux and vortex motion, and nonequilibrium quasiparticles – generate the 1/f flux
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obtaining detailed structural information on active pharmaceutical ingredients (APIs), pharmaceutical cocrystals and salts, formulated drug products, and other complex solid-state systems. Projects
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nationally recognized leader in crop production, plant breeding, genetics, soil science, and sustainable agricultural systems. The department conducts innovative research that addresses global challenges in
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diagnostic assay development. Research areas include investigating the regulation of streptococcal peptide systems, applying artificial intelligence approaches to design novel antimicrobial peptides