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Field
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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modulation, radar/sonar signal processing, and machine and deep learning. WORK PERFORMING: Individual will perform research generally in the area of statistical signal and array processing. Topics of specific
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communication signals on our mental processes. What you will do Build novel deep learning architectures for auditory prediction (speech and/or music) prioritizing explainability and cognitive hierarchies Quantify
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partners, or translational research teams. Experience with Quarto, Python, and/or other programming languages. Experience and interest in data science or informatics education. Experience with deep learning
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in
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required Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow) Experience with unstructured
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. Demonstrated experience in either of the following areas (a) data science, (b) theoretical nuclear reaction models and/or (c) deep learning-based machine learning and applications of artificial intelligence
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection