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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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include: Biomedical sensing and physiological monitoring Edge intelligence and energy-efficient machine learning hardware Radar and wireless signal processing and communications The successful candidate
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pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 19 hours ago
or machine learning applied to plant traits. Candidates with strong quantitative skills, interest in interdisciplinary collaboration, and motivation to explore crop performance in novel environments may find
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing spontaneous versus precipitated withdrawal episodes. The spontaneous vs
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well as exploring the application of research findings to advanced 3D models such as organoids and 3D bioprinted tissues Learning about high-content, automated phenotypic drug screening pipelines against high
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spectral based sensing, including Ultrasound and Hyperspectral Imaging (HSI), Artificial Intelligence (AI) and Tiny Machine Learning (TinyML). Duties As a Postdoctoral researcher you are expected to perform
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computing and artificial intelligence. Areas of interest include, but are not limited to, the following: Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks