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at UCLA The Peng Lab at the University of California, Los Angeles, is seeking highly motivated Postdoctoral Scholars with expertise in data science and bioinformatics to drive groundbreaking discoveries in
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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Library and Museum, and much more await you. Experience all that a big city has to offer but with a reasonable cost-of-living and no long commutes. Medical, prescription drug, dental, vision, life and
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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, resume, and contact information for three professional references (to include at least one previous supervisor) are strongly recommended. You may upload all three on the application under CV/Resume or upon
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both qualitative and quantitative data and coordinating findings across data sources. The postdoctoral research associate will have opportunities to publish emerging findings from these research studies
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countries to increase opportunities for discovery. We and our partners aim to integrate state-of-art data science with various types of statistical methods to translate large medical data from benchwork
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learning, and data modeling techniques Preferred: Prior working experience with EHR data, machine learning, deep learning, imaging informatics, and large language models (LLM) is preferred. Prior working
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skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: mouse survival surgery, two-photon microscopy and analysis, patch-clamp recording, single
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, including fitting and manipulation of large array-type data sets (using Python, Matlab or equivalent) Ability to communicate well, and work within a collaborative team environment Preferred Knowledge, Skills