666 deep-learning "MIT" positions at Princeton University in United States

Assistant Director, Learning Programs

-cognitive perspectives on all students, including first-generation, low-income students Deep understanding of student development, learning theory, processes, and methods Excellence in consulting and

Postdoctoral Research Associate - Interfacing machine learning with climate models

- Interfacing machine learning with climate models Company: Princeton University Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid

STEM Learning Fellow

Details Posted: 01-Apr-24 Location: Princeton, NJ, US, 08544 Type: Full-time Salary: Open Categories: Other Staff/Administrative Internal Number: 238868208 STEM Learning Fellow US-NJ-Princeton Job

Postdoctoral Research Associate - Interfacing machine learning with climate models

- Interfacing machine learning with climate models Company: Princeton University Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid

Postdoctoral Research Associate - Interfacing machine learning with climate models

conduct research on the use of machine learning in ocean climate models. The goal is to demonstrate the successful use of machine learned parameterizations of unresolved processes that will reduce biases in

Postdoctoral Research Associate - AI/Machine Learning for Illicit Drug Identification

approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a range of exciting projects

Ocean Surface Boundary Layer Mixing Parameterizations using Machine Learning

conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve

Improving Ocean Surface Boundary Layer Mixing Parameterizations using Machine Learning

conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve

Lecturer in Theater

, Performance Art, and Theatrical Design. Competitive candidates will be active teachers, practitioners and/or scholars with a national reputation who demonstrate a deep commitment to undergraduate teaching and

Lecturer in Dance

/choreographer is required. Individuals who can demonstrate a deep commitment to undergraduate teaching and advising are preferred. These positions are subject to the University's background check policy