70 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Johns Hopkins University
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to improve the early detection of pancreatic tumors and improve patient management. Different machine-learning approaches will be compared, and models validated on data prospectively collected. The position
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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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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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computer programs to review data. Assist with data cleaning measures to ensure accuracy of data and preparation of tables. Lead basic activities such as data collection and data entry. May lead specific
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fields. Individuals in this position will perform technical work supporting the collaboration's scientific research. Research Title: Postdoctoral Researcher Applying Machine Learning Methodologies
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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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- 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
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) equipped with a cryogenic stage for surface analysis - Develop computer code (e.g. Python) for the development and analysis of optical cavities Qualifications § PhD degree in Materials, Electrical