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technical ideas, and engaging with GenAI industry and open-source communities. Job Responsibilities: Conduct the research in AI/ML domains, especially in probabilistic ML and scalable sequence network
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community, and develop their teaching and research-leadership experience. Engagement with Dstl, project partners and relevant industry and government stakeholders will help the Fellows build external networks
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policy, research and more? Do you want to develop skills within and outside of your field of study and interest and earn a competitive edge? Do you want to network with your peers, travel, and participate
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to develop research themes at the forefront of modern science A friendly, inclusive, and collaborative international working environment that values diverse perspectives Access to a strong network of top-level
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex network models to partially observed hospital infection data, leveraging patient movement data. This research will
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 14 hours ago
regression, principal component analysis, and artificial neural networks — to determine optimal modeling frameworks for high-dimensional in vitro data generated by platforms such as organ-on-a-chip systems and
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to develop research themes at the forefront of modern science A friendly, inclusive, and collaborative international working environment that values diverse perspectives Access to a strong network of top-level
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networks at reputable international conferences Mentor graduate students and report to PI as required Organize internal events (reading groups, seminars, etc.) as required Perform teaching and invigilation
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Outcome Network (ICON) on an NIHR-funded Better Methods, Better Research (BMBR) project developing the Multiple imputation framework for missing data. This collaboration with University of Warwick, aims
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with GenAI industry and open-source communities. Key Responsibilities: Conduct the research in AI/ML domains, especially in probabilistic ML and scalable sequence network architectures Produce academic