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Field
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Job Description Project Description We invite applications for a postdoctoral position in experimental mass spectrometry-based proteomics, focused on peptide ionization, charge state behavior, and
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(ISMaRT, https://sites.google.com/view/ismart-iastate ). A complete application will consist of a cover letter, a current CV, a research statement, a teaching statement, and three references. All
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collaborative environment with projects and interactions spanning multiple labs within the group, across NIST and externally. Candidates should have a PhD in physics, electrical engineering, mechanical
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. The postdoctoral project is part of our current activities on developing new antibiotics based on pleuromutilins. The goal of this project is to identify a hit compound specifically targeting multi-resistant Gram
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this position, you will ideally bring the following: For the Networking and AI position: Completed a PhD in Computer Science, Electrical & Computer Engineering, or a closely related field Expert knowledge of deep
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computational approaches for high-dimensional data analysis. https://www.epelmanlab.com/ http://www.uhnresearch.ca/researcher/slava-epelman @EpelmanLab This role has direct mentorship and guidance in grant
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
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quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between senior staff, PostDocs and PhD/Master students
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expertise/interest in Bayesian methods for addressing measurement error. Ideally PhD within the last 5 years. Advanced level experience with R, desired knowledge of Nimble, Overleaf. Excellent communication