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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference
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; DNA sequencing; De novo assembly; Machine learning; Reference materials; Precision medicine; Data science; Artificial intelligence Eligibility citizenship Open to U.S. citizens level Open to
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research results in leading international conferences and journals in machine learning, computational biology, and AI for science The postdoc will work at the interface of machine learning, genomics, and
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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their research careers. They would also be expected to help seek external funding for their work. The postdoc will receive close one-on-one mentoring, opportunities to present results at conferences, and guidance
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molecular biology and cell biology techniques. Basic procedures include but are not limited to: pipetting; cell and tissue culture, handling of small laboratory animals, etc. There will be continuous learning
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Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep learning, with experience in time series forecasting or related
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measurement technique development, atmospheric modelling, and advanced methods for integrating observational and model data through data assimilation and machine learning. About the research project The overall
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meetings and read literature applicable to the research area Analyze data using standard and machine learning algorithm Maintain a lab notebook of raw data and organize data for analysis by senior lab
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on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing and quantum