354 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs at Nature Careers
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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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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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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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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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Screening Process: Deadline for application: May 17, 2026, 23:59 (JST) Document Screening: Late June to Late September 2026 Interview: December 5, 2026 Other Details: Please visit our website (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
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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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Learning III. Knowledge Exchange and Services IV. Research (basic science, translational and/or clinical research) Preference will be given to those with demonstrated administrative contributions and
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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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contribution of the PhD will be the derivation of multilayered approaches for motion planning and control based on the XS-Graphs, where both model-based and learning-based solutions are foreseen. This includes