87 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" positions at Nature Careers in United Kingdom
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and we strive to build a workplace where everyone feels a sense of belonging. All new staff who join us learn about the importance of diversity and inclusion to the Museum and how to contribute
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to traverse genes and complete transcription, as well as those that abort this process by removing or destroying Pol II on genes e.g. https://doi.org/10.64898/2025.12.04.692291 ; https://doi.org/10.1016
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products, platforms and services that help researchers to uncover new ideas and share their discoveries, health professionals to stay at the forefront of medical science, and educators to advance learning
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About us The UCL Laboratory for Molecular Cell Biology (LMCB, http:/www.ucl.ac.uk/lmcb) is an internationally renowned, multidisciplinary, molecular and cell biology department, located in the heart
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. You will work on developing and applying foundational methods for the synthesis of large genomes, specifically the human genome. For further background information see https://www3.mrc-lmb.cam.ac.uk
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-performing culture across the facilities. About the Scientific Core Facilities & Services Please visit our website to view information about our Facilities: https://www.cruk.manchester.ac.uk/facilities/ About
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We have an exciting research opportunity for a Research Assistant / Associate tojoin our team. The post holder will be based at the Cancer Research UK-Scotland Institute (CRUK-SI) in Glasgow https
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qualifications. Further information about the benefits available can be found at http://www.discover.ukri.org/benefits-of-working-at-ukri . The LMB is a world-class research institute within UK Research and
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on the lab: https://www.pdn.cam.ac.uk/directory/ewa-paluch and https://paluchlab.uk Fixed-term: The funds for this post are available for 2 years in the first instance. To apply online for this vacancy and to
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the synaptic wiring diagram, or connectome, of whole brains, designing, building and using machine learning approaches to computer vision as applied to volume electron microscopy of whole brains. The ideal