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Field
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Details Title Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems) School Harvard John A. Paulson School of Engineering
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Posting Details Posting Details Logo Institution South Dakota Mines Working Title Postdoctoral Researcher Posting Number NFE02992P Department SDSMT-Chemistry, Biology, and Health Sciences 1 Physical
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strong focus on (deep) machine learning are: Trustworthy and interpretable AI with uncertainty quantification Detection and characterization ofsub-visible particles in microscopy images
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: Job Requirements: Required: PhD in computer science, biomedical informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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approaches applied to different science domains, such as chemistry, materials, physics, imaging, drug discovery, climate/weather forecast, etc. Knowledge of implicit deep learning models (NERF, neural
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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collaboration with the Reiser Lab (HHMI Janelia) and the Schnitzer Lab (Stanford University; HHMI) is seeking a postdoctoral researcher with a strong background in robotics, mechatronics, systems engineering
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-grade AI implementation frameworks and system architecture into a unified translational ecosystem. This effort is conducted through a deep strategic partnership with Cook Children’s Health Care System
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spectral imaging, lifetime data, or multi-channel image datasets. Solid background in chemometrics, machine learning, or deep learning, particularly for classification, clustering, or pattern recognition in