355 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs at Nature Careers
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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suite of technologies for studying protein aggregation, including advanced biophysical, ultrastructural, and cell‑biological platforms. Learn more about us on our website and don’t miss the laboratory
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T cell biology or cancer immunology, and programming skills (R, Python) for data analysis. Please also read recent manuscripts published in the last two years 2024 Nature: (https://www.nature.com
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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
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publication record in immunology/epigenetics. Information on our postdoctoral training program, benefits, and a virtual tour can be found at http://www.utsouthwestern.edu/postdocs . Please also read recent
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(https://irp.drugabuse.gov/staff-members/da-ting-lin/ ) Note: This position is open to both U.S. and non-U.S. citizens. Selection for this position will be based solely on merit, with no discrimination
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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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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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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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understanding and generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research