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eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary Outstanding applicants are desired for a Part-Time Lecturer (PTL) teaching position as Co-Course Director for a
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SAF combustion. Recent advances have demonstrated that machine learning techniques, particularly neural networks, can significantly accelerate chemical kinetics computations. Nevertheless, most of
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comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run numerical simulations on NYUAD’s High-Performance Computing (HPC) system. Support
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fabrication and materials research. They function to give students an intimidation-free and safe learning environment, equipped with modern technologies in support of the curriculum, with which they can
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen
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technical support and/or sales of computers and supporting software. Excellent customer service skills. Ability to learn the computerized inventory control/accounting/point-of-sale system. Ability to become
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review activities; Teach and evaluate medical students, psychiatry residents, fellows, and allied health professional fellows/students/trainees in both clinical activities at University Hospital as
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Applications: Microsoft Excel, Microsoft Word, Microsoft Outlook Required Other Computer Applications: Required Additional Knowledge, Skills and Abilities: Demonstrate organizational skills with ability to work
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computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI