963 machine-learning-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" Fellowship positions
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric methods to extract meaningful biological insights from multivariate data and complex GCxGC-TOFMS datasets
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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for real-time surveillance and precision applications. Learning Objectives: The candidate will gain hands-on experience and advanced knowledge in utilizing cutting-edge geospatial tools, including UAV-based
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invaluable hands-on experience and develop advanced skills while working closely with the Research Entomologist throughout all phases of the research process. This opportunity will allow you to learn and
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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 22 hours ago
hardware protocols (e.g., PCIe), computer architecture, or systems security. ● Understanding of vulnerability analysis or anomaly detection. Duties and Responsibilities A Postdoctoral Fellow (""postdoc"") is
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nowcasting platform that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative