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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and
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about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking
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conditions, and brain tissue microstructure and functioning. The successful candidate will be working within a multi-disciplinary team of MRI physicists, computer scientists, radiologists, neuroscientists, and
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the geography of outdoor activities and psychological stress. Duties/Responsibilities The researchers will contribute specifically through: Gathering data, developing and implementing machine learning models, and
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
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focus in machine learning. The postdoctoral scholar will work on topics of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine
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equipment using a machine shop Expertise in reduced-order modeling of plasmas, including plasma chemistry. Instructions For full consideration, applicants should submit via Interfolio, the following by
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). • Familiarity with cloud computing and machine learning techniques. Instructions Applications for this position should include a: (1) Curriculum Vitae with the names and contact information of 3 references (2
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industrial engineering, systems engineering, computer science, electrical engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big