261 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at Nature Careers
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pediatric cancers. In prior work, we have developed tools and methods to map the cellular diversity of pediatric tumors by adapting single-cell sequencing techniques to archival frozen tumors. In that work
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Postdoctoral Research Associate - Training in Pediatric Cancer Survivorship Outcomes and Interventio
; a top-ranked scientific environment; and superb benefits, mentoring, and professional development. Positions are available in diverse research areas, including epidemiology, genetics, computational
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stem cells Develop computational approaches for integrating metabolomics, transcriptomics, and genomics datasets across development and disease Candidates must hold a Ph.D. and/or M.D. degree with a
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biology, computational biology, in vivo models of disease, and pre-clinical study development. You will have the opportunity to develop and lead projects using several cutting-edge model systems including
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human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
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new method for lncRNA gene identification from whole genome sequences. Collaborating with experimental researchers to integrate computational findings/tools with functional investigation. Scientific
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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program. Through this work, you will build scientific independence, develop new science and leadership skills, and establish a growing reputation externally. Your role will be to lead a research project
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and to identify new therapeutic targets and prognostic biomarkers. Novel data integration methods allow to identify signatures of retinal cell types in liquid biopsies without the need for a direct