61 machine-learning "https:" "https:" "https:" uni jobs at Johns Hopkins University in United States
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and image analysis within the project, responsible for designing and iterating on machine learning architectures, managing training pipelines and datasets, and optimizing models for deployment across
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consultations. Acquire medical/psychiatric records of patients. Relay information to patients regarding preparation for laboratory tests and examinations. Maintain familiarity with various types of medical
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-on laboratory skills and troubleshooting mindset - Mechanical design and rapid prototyping (CAD, machining, 3D printing) - Instrumentation integration (sensors, cameras, data acquisition systems
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performances. Machines and/or equipment used on the job Operate a variety of machines and equipment including automobiles, vans, office equipment, radio, telephone. Must qualify with Baton / OC Pepper spray
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Outstanding organization, with attention to detail and the ability to prioritize multiple responsibilities. Excellent computer skills with sound knowledge of MS Office Suite, especially Excel, and database
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structures, and time-dependent processes spanning molecular and cellular scales. We encourage the use of theory and computation as well as experiment, and welcome applicants who use machine-learning and
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performances. Machines and/or equipment used on the job Operate a variety of machines and equipment including automobiles, vans, office equipment, radio, telephone. Must qualify with Baton / OC Pepper spray
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- Knowledge of mathematical probability and statistics, and optimization methods - Knowledge of machine learning, including supervised and unsupervised learning, deep learning, and model evaluation - Knowledge
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representativeness - Knowledge of software engineering for AI applications - Knowledge of mathematical probability and statistics and optimization methods - Knowledge of machine learning including
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scientific database software - Demonstrated expertise in chemical structure analysis by computer - Demonstrated facility in applying mass spectral fragmentation rules for electron ionization