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experience with machine learning frameworks such as PyTorch or scikit-learn. You are a team player and a team leader: you can mentor PhD students and Bachelor students effectively. You share your knowledge
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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PhD in Data Science, Computational Social Science, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning
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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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project activities and writing reports Your Profile MSc or PhD in a relevant field Experience with Machine Learning modeling Coding experience, preferably Python Basic knowledge of databases tools and
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 10 days ago
, machine learning and statistical methods to elevate impacts research. There is also opportunity to work at the nexus of water and agriculture, as well as in risk management for suburban landscapes. Location