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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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engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big data. · At least one year of research experience in transportation
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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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or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion). ? Familiarity with cloud computing and machine learning techniques
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Scholar appointments to a total of five years, including postdoctoral experience(s) at other institutions. The University of Washington and the International Union, Automobile, Aerospace and Agricultural
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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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machine vision approaches, coupled with a strong interest in evolutionary questions. Preferred Qualifications Education: No additional education unless stated elsewhere in the job posting. Certifications
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. Experience with high-throughput molecular biology assays. Experience with complex functional experiments. Background in machine learning, AI, or data integration for genomic datasets. Familiarity with gene
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dedicated to understanding the molecular mechanisms of ATP-dependent AAA+ proteolytic machines in both bacterial systems and human mitochondria, exploring how these complexes form and achieve substrate
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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