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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the
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University of California, Los Angeles | Los Angeles, California | United States | about 23 hours ago
seeking applicants for a full-time postdoctoral scholar position in Computational Immunology and Genomics. The successful candidate will develop and apply computational, statistical, and machine-learning
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chromatography. The candidate will prepare samples for immunopeptidomics by liquid chromatography coupled with mass spectrometry tandem (LC-MS/MS), analyze large datasets, and develop scripts and machine learning
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Intelligence and Machine Learning, Computational Statistics, Random Matrices, Free Probability, Stochastic Control, Mathematical Finance, Stochastic Partial Differential Equations, Markov Processes, Branching
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/communications, machine learning/vision, intelligent transportation systems, intelligent sensing/localization, or signal processing. In line with our Athena SWAN ambitions we especially encourage women to apply
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot