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the application of machine learning techniques (e.g., doc2vec, encoder models, multi-modal embeddings, large language models) to map concepts and their relationships, tracing how they change, merge, or diverge
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preclinical transplant models and human transplant recipients to develop and test precision immunotherapeutic approaches in the field of transplantation, metabolic disorders, and other diseases. About the Study
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machine learning analyses will be performed to determine correlations across stimulation settings and body systems as well as to develop predictive models and biomarkers for physiological and clinical
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nuclear physics detectors. Experience analyzing data from high energy or nuclear physics experiments. Familiarity with Monte Carlo simulations. Familiarity with machine learning techniques. About the
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demonstrated experience with a set of tools appropriate for working with large-scale data science including application of machine learning. In addition, applicants must have demonstrated leadership experience
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, computer vision in the Division of Health Data Science (HDS) at the DOS. The position is an annually renewable professional academic appointment. Duties/Responsibilities: ● Risk predictive model for clinical