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Field
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integrates OLA production of liposomes, trap arrays, local light/heating modules, and selection and sorting routines. Guided by machine learning, we will perform directed evolution experiments where we
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algorithms; experience in 3D/4D (X-ray tomography) image processing; experience in machine-/deep-learning based image analysis; knowledge of tomographic reconstruction methods; experience in materials research
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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of dehydration. Upon these experimental study, we will develop a working prototype with all proposed functionalities. The proposed system will be the first wearable dehydration sensor targeting
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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national human rights courts, tribunals, mechanisms, and transitional justice processes, and propose potential pathways to justice for victims. This position relates to the second part of the project
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high intellectual merit and the willingness to use machine learning and/or AI techniques. Essential Duties and Responsibilities: Successful candidates are expected to develop an impactful research
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is