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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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skills in computational and data analytical methodology development and implementation; experience in supervised and unsupervised machine learning, low-dimensional models or deep learning models, and
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the lab of Dr. Christina Nicholas, University of Illinois Chicago College of Dentistry. The Nicholas Lab applies deep phenotyping approaches to clinical, anthropological, and evolutionary questions
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. His expertise includes: Developing novel deep learning and machine learning algorithms for biomedical and health applications. Applying responsible AI principles to ensure privacy-aware and
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or prior experience with multilingual or low-resource NLP Programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and their application in high-performance
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survival data using longitudinal features, and (6) machine learning and deep learning for analyzing time-to-event outcomes, or (7) radiomics and medical imaging analysis. Required Qualifications: We seek
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development and application of deep learning methods, with a strong interest in understanding molecular mechanisms of disease. The position will be highly collaborative working with a diverse group of
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you will extend this work to the ultrasonic sounds of bats, insects and other animals. This involves curating open datasets of sound, as well as training deep learning, and validating that these methods
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AI hardware to help solve significant real-world problems using machine learning and deep learning. ALCF researchers work in a highly collaborative environment involving science application teams
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that provides an understanding of the mission, operations, and culture of DOE. As a result, fellows will gain deep insight into the federal government's role in the creation and implementation of energy