20 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Southern California
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, information processing, computing, cybersecurity, and communications technologies. ISI’s 400 faculty, professional staff and graduate students carry out extraordinary information sciences research at three
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Alzheimer’s disease (AD). Our researchers integrate brain mapping techniques with machine intelligence and computational biology approaches to investigate how brain alterations contribute to neurocognitive
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Organization Planning Project management Research Strong computer/software skills The annual base salary range for this position is $62,400 - $67,000. When extending an offer of employment, the University
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of genomic, epigenomic, and transcriptomic data processing and analysis, expertise in multi-omics data integration, and working experience with computational modeling and machine learning. The ideal candidate
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integration, and working knowledge of computational modeling and machine learning. The ideal candidate will be able to analyze high dimensional sequencing data, perform network-based analysis (e.g. , WGCNA) and
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publishing scientific manuscripts under the direction of the Principal Investigator Responsible for teaching techniques to other lab members Preferred Qualifications Possess a PhD or be close to the completion
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program development. We are seeking established individuals who thrive in contemporary interdisciplinary academic arenas, can produce impactful findings, and facilitate knowledge translation to critical
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populations. In this position, we are looking for a postdoctoral researcher with strong computational background for method development in population and statistical genetics. The position is funded by an NIH
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possible when every member of the Dornsife community owns their role as a steward of the culture in which we learn, research, and work; when we believe that it is because of who we are that we are able to do
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vulnerability. We are further integrating advanced computational methodologies and cutting-edge genomic tools to strengthen these models. Successful candidates will lead projects, from designing projects