13 machine-learning-"https:" "https:" "https:" "RAEGE Az" Fellowship positions at Johns Hopkins University
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Computer/Information Sciences Internal Number: A-179059-11 General Description The Johns Hopkins University Data Science and AI (DSAI) Institute welcomes applications for its Postdoctoral Fellowship program
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modeling, machine learning methods, and applications involving text and other non-traditional data sources. The fellow will contribute to and extend research in these areas, engaging in projects that develop
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for understanding complex economic and financial systems. Research Areas: Applied statistics and econometrics with emphasis on high-dimensional data analysis, forecasting and predictive modeling, machine learning
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§ Experience in the collection and processing of TEM/STEM data § Computer programming for custom data processing § Strong oral and written communication skills. Application Instructions Please upload
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members of underrepresented groups. Application Materials Required: Further Info: http://physics-astronomy.jhu.edu/ 410-516-7346 The Johns Hopkins University Department of Physics and Astronomy 3400 N
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grounded in exploration and discovery. Hopkins students are challenged not just to learn but also to advance learning itself. Critical thinking, problem solving, creativity, and entrepreneurship are all
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the Ancient Americas to begin July 1, 2026. Fellows will teach one class each semester (undergraduate or graduate) and participate fully in the life of the department and university. We encourage applications
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) and their families. This 12-month post-professional program is focused in the outpatient neurorehabilitation setting, with experiential learning opportunities in acute care and inpatient rehabilitation
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grounded in exploration and discovery. Hopkins students are challenged not just to learn but also to advance learning itself. Critical thinking, problem solving, creativity, and entrepreneurship are all
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consisting of weekly skills lab, two weekend learning modules, and online learning Evidence-based independent self-study and research for a case presentation or a quality improvement project in upper extremity