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the complexities of the human regulome through advanced cell-free DNA profiling and developing cutting-edge computational algorithms and molecular profiling techniques. Our research focuses on early cancer detection
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omics to advance biological and clinical discoveries and develop next-generation theragnostics. The postdoctoral fellows will mainly focus on (1) creating novel computational algorithms to analyze and
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sensor networks, robotics, energy, and Smart Cities • Network systems and economics, cooperative control and optimization, game theory • Distributed algorithms for decision making • Machine learning and
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molecular biology. This research opportunity will be focused primarily on developing tightly integrated sequencing experiments and computational algorithms to characterize biomolecular interactions with high
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for robotics Robotics simulation and synthetic data generation Robot manipulation Deep learning-based planning You preferably have experience working in a biology or chemistry laboratory environment
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single-cell sequencing, spatial transcriptomics, and machine learning algorithms to to understand, at the tissue and organ level, how specific cellular communications—from synaptic connectivity to neural
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funded by an NIH R01 and will focus on developing digital biomarkers for early detection of neurodegeneration using single-channel sleep EEG. Candidates with a strong background in computational biology
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of the following: Ecosystem Modeling, Machine Learning, Microbiome, Microbial Ecology, Soil Science, or Computational Biology. The positions are for several different projects, including the following: (P1
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Postdoctoral Researcher in Bioinformatics & Computational Biology University of Oklahoma Norman Campus: Gallogly College of Engineering: School of Computer Science Location University of Oklahoma