52 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions at Nature Careers in United States
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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, or methodologies in bioengineering. This search has a particular focus in immunology, neuroscience, and/or computational science/machine learning. That said, we give high priority to the overall originality and
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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to build the strongest possible university with the widest reach. To learn more about the Arts & Science commitment to inclusive excellence, please read here: https://as.nyu.edu/departments
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, machine learning, and data-driven modeling methods, physiology, transport, fluid and solid mechanics, systems analysis, circuit prototyping, technology transfer, and biomedical design practices, in
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of California, Santa Cruz, invites applications for a UC Cooperative Extension (UCCE) Specialist at the Assistant rank. For full description, please follow https://recruit.ucanr.edu/JPF00368 This position will
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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, machine learning model applications, and real-time applications Opportunities to learn more about systems neuroscience and neuroengineering One on one mentorship with graduate students and postdocs
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to investigate the uterine endometrium and maternal-fetal interface, with the goal of improving female and fetal health. More information about the lab and their work can be found by visiting https