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Field
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* Design, implement, and evaluate wireless-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide
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the molecular biology of aging and neurodegenerative diseases. Engage in the development and testing/validation of new algorithms and their applications to transcriptomic, epigenomic, genetic, and proteomic data
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strategies Design of user-friendly tools for the identification of unknown compounds from the spectral datasets utilizing various computer algorithms and artificial intelligence tools Participation in high
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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experimental cycle from real-time X-ray measurements to post-experiment reconstruction: Develop learning-enabled algorithms for 3D reconstruction of noisy and heterogeneous synchrotron datasets. Implement
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, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno-economic study, design and analysis of integrated systems. Experience with energy system
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | about 16 hours ago
segmentation/classification/quantification/chatbot tasks. Learning Objectives: Under the guidance of an FDA mentor, you will: Develop comprehensive expertise in evaluating artificial intelligence algorithms
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. This longitudinal project investigates the implementation of AI-empowered chronic disease management systems in hospitals. It examines human-AI collaboration and the "boundaries of work" between humans and algorithms
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sensitivity analyses across pathology severity, body morphology, camera viewpoint, and environmental conditions Develop a single-camera, home-based markerless system Test the algorithm across lab and home