251 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral research jobs at Nature Careers
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: https://www.list.lu/ How will you contribute? This postdoctoral position is part of a large European project involving universities, research institutions, and industrial partners across Europe
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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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project aimed at advancing our single-cell ribosome profiling technologies in cancer. For further information about the lab, please visit https://www.sendoellab.org/. The Institute for Regenerative Medicine
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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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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
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application instructions), please visit: https://www.mpg.de/en/max-planck-postdoc-program . To submit your application online, please visit: https://postdocprogram.mpg.de The application deadline is April 13
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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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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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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