342 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" research jobs at Nature Careers
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image/signal processing, particularly in computer vision.Strong programming skills and experience with at least one deep learning framework e.g. TensorFlow or PyTorchFamiliarity with machine learning and
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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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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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computational approaches for high-dimensional data analysis. https://www.epelmanlab.com/ http://www.uhnresearch.ca/researcher/slava-epelman @EpelmanLab This role has direct mentorship and guidance in grant
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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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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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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University is committed to fostering gender equality in research and encourages women to apply. Scientists at risk are encouraged to apply. How to Apply Application website: https://cuni.cz/UKEN-2187.html