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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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Research Assistant or Postdoctoral Research Associate About the Role The School of Electronic Engineering and Computer Science at Queen Mary University of London seeks to recruit a Research
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control, network optimization, or joint communication and sensing is highly desirable. Experience with artificial intelligence, machine learning, reinforcement learning, or optimization techniques applied
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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impact? We are currently seeking a/an University Assistant postdoctoral 49 Faculty of Social Sciences Startdate: 01.11.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b
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The postdoctoral associate will be embedded in a collaborative research environment that brings together expertise in functional genomics, regulatory genomics, machine learning, population genetics, and human
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across learning sciences, computer science, machine learning, HCI and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and