428 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at Nature Careers in United States
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of Biomedical Engineering (BME) is situated within https://www.lerner.ccf.org/ ). 2025, over 1,800 people (including about 235 principal investigators and 650 trainees) participate in research programs focusing
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responses in the heart. Read more about Dr. Fang's research in ISHR award brochure: https://cdn.ymaws.com/ishrworld.org/resource/resmgr/pdf/oia_brochure_fang_2025_final.pdf ). Dr. Fang is committed
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The Jiang Lab (https://labs.icahn.mssm.edu/jianglab/) at the Icahn School of Medicine at Mount Sinai, New York is seeking a highly motivated postdoctoral fellow with expertise in genome editing
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Biology Scientist in Single-cell omics & AI to support the valorization trajectory of a computational platform combining single‑cell omics, AI machine learning, and translational biology. The role involves
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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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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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a postdoctoral scholar in computational biology. The PI, Dr. Lixing Yang is an Associate Professor at the Ben May Department for Cancer Research and the Department of Human Genetics. To learn more
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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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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome