217 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Zintellect
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Organization DEVCOM Army Research Laboratory Reference Code ARL-C-CISD-300144 Description About the Research Current approaches optimize machine learning training largely by exploiting Deep Neural
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collection of streaming sensor data. This project focuses on utilizing state-of-the-art reinforcement algorithms to 1) dynamically learn from multi-agent actions and context, 2) evaluate the environment and
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-Docs, post-Bacs, summer internships, etc.) to those interested in research in the following fields: Theory and application of machine learning and artificial intelligence including Natural
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-property relationships, statistics and probability, applied mathematics, data science, or machine learning. Application Requirements A complete application consists of: Zintellect Profile Educational and
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pathology whole slide image analysis are encouraged to apply. Additional preferred skills: Python programming Pathology whole slide image analysis Machine learning, especially generative adversarial networks
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to evaluate autonomous surgical robotics, mixed reality medical applications, and phantom-based alternatives. This project provides extensive learning and development opportunities across three critical areas
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analysis of laboratory assay readouts, or processing and analyzing transcriptomics data (bulk or single-cell RNA-seq). Learning Objectives: Under the guidance of a mentor, the participant will have the
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and
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, statistics, and field-lab approaches. Learning Objectives: The participant will receive training in plant molecular biology, genetics, and genomics. This research is expected to result in increased learning
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Sensing Nuclear Science and Weapon Effects Artificial Intelligence, Machine Learning, and Cyber Security Materials, Extreme Environments, and Optical Sciences Remote Sensing and Radiation Detection