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Postdoctoral Research Scholar in Machine Learning and Computational Genomics Department of Epidemiology, School of Public Health, University of Pittsburgh The Department of Epidemiology
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FieldComputer science » OtherEducation LevelPhD or equivalent Skills/Qualifications CANDIDATE ’S PROFILE The candidate should possess a PhD in machine learning or computer vision and have a strong publication
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of their research projects, fellows in the Smith lab have the opportunity to work one on one with the PhD biostatistician associated with our laboratory to learn introductory machine learning methodology such as
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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Car Parking On site dining facilities On site TFI Bike Sharing Station Eligibility criteria Essential: Hold a PhD in a relevant discipline at the contract start date. Relevant research experience. Self
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
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the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group