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-making. Among the key duties of this position are the following: Develop and refine computational models (e.g., mechanistic, machine learning, or hybrid approaches) for ICU patients. Integrate and analyze
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position) Designing a machine-learning-based bias correction method using retrospective forecasts and reanalysis data for comparative calibration. Topic 3: Development of seasonal prediction models (one–two
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Requisition Id 15358 Overview: Oak Ridge National Laboratory (ORNL) is seeking an ambitious postdoctoral scientist with keen interest in artificial intelligence (AI) / machine learning (ML) and
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analyze and interpret multi-omic data to identify spatial patterns, cellular neighborhoods, and gene programs associated with drug resistance. Develop predictive models to infer tumor evolution and
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, scikit-learn, TensorFlow, PyTorch). Hands-on experience with data science workflows, including ML/AI model development, training, and evaluation for predictive analytics or decision support. Excellent oral
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technologies—and eager to accelerate their discovery with machine learning and materials theory? Are you passionate about linking atomistic processes to device performance through computer simulations? Are you
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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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expertise in the area of prediction of both costs and benefits of retraining or finetuning machine learning models in application domains including financial fraud detection and machine translation
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values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker
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have: Expertise in processing optical remote sensing data over large areas and using machine learning models for predicting ecological metrics Strong background in remote sensing in hyperspectral imaging