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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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datasets Implement LLM and Machine Learning algorithm Conduct statistical analysis in SAS or Stata Assistant with other ad hoc tasks Required Education Bachelor’s or Master’s degree in computer science
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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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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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Description The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence, machine
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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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Science, or Information Science, or a bachelor’s degree with several years of experience and expertise in their field. The position requires experience with at least one of the following: Data Science, Machine Learning
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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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centers and institutes, nearly 300 full-time faculty and close to six thousand students. NYU's dynamic Global Network includes NYU Abu Dhabi, NYU Shanghai, and international programs and academic centers