19 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" Postdoctoral positions at Nature Careers in United States
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or datasets for metabolite discovery from small molecule mass spectrometry (e.g., https://www.nature.com/articles/s41586-025-09969-x, https://www.nature.com/articles/s42256-021-00407-x, https://www.nature.com
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T cell biology or cancer immunology, and programming skills (R, Python) for data analysis. Please also read recent manuscripts published in the last two years 2024 Nature: (https://www.nature.com
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publication record in immunology/epigenetics. Information on our postdoctoral training program, benefits, and a virtual tour can be found at http://www.utsouthwestern.edu/postdocs . Please also read recent
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stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. The Clurman lab (https://research.fredhutch.org/clurman/en.html works at the intersection of two
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on oral health. Preferred Qualifications: Experience analyzing oral microbiome datasets (16S, shotgun metagenomics, or metatranscriptomics). Advanced programming and data science skills in R, Python
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
. We seek highly motivated scientists with expertise in computational genomics/AI and/or translational cancer biology to join our dynamic, well-funded research program at the frontier of cancer genetics
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Postdoctoral Fellows to join a dynamic, fully funded research program investigating how environmental exposures and inflammation drive hematopoietic stem cell dysfunction, clonal hematopoiesis, and the
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2021; Khoshkhoo et al. JAMA Neurology 2023; Farrell et al. Nature 2024; Bizzotto et al. PNAS 2025; Khoshkhoo et al. bioRxiv 2026. For more information, please check our websites at https
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regulation. We are also actively studying the role of non-canonical translation events in antiviral immunity. The Subramaniam lab is part of the Basic Sciences Division and the Computational Biology Program at
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. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https