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Field
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and
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pathophysiological mechanisms for acute organ injury research under POI-KB. · Authorship of high-impact first-author or co-author manuscripts in leading informatics and machine learning journals and conferences
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analysis and application of machine learning techniques to structured numerical and unstructured textual data; (d) have a good track record of academic writing, including report writing, manuscript
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Ph.D. in neurobiology or a related field. 1 year post-doctoral experience Certificates/Credentials/Licenses Applicants must have a Ph.D. in neurobiology or a related field Computer Skills
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will have a strong research record in NLP, machine learning, or closely related areas, along with excellent communication and collaboration skills. We are especially interested in candidates with strong
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. · Knowledge of molecular biology, cell biology, immunology, neuroscience, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning
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, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning, artificial intelligence, or translational biomedical research is considered
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Successful candidates will have publications in information theory and machine learning venues, such as IEEE Transactions on Information Theory, ISIT, NeurIPS, ICML, ICLR, and ACM FAccT. Experience in machine
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mathematical structures and computational algorithms underlying modern machine learning and artificial intelligence. Relevant themes include geometric and algebraic methods for learning, structure-preserving
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managing diabetes using computer simulation models. Learning Objectives: You will learn: How to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and