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. Responsibilities include conceptualizing and implementing statistical and structural models, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis
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workflows; GenAI based algorithm and agent development for causality assessment; Web-based tool development for the support of dataset collection; Performance evaluation and validation for the developed AI
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 14 days ago
Medical Dictionary for Regulatory Activities (MedDRA)-based search algorithms compared to a novel algorithm that leverages other features (e.g., patient age) for identification of cases of prenatal drug
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specialization. Develops understanding and skills to allow for completion of assignments that cross fields of specialization. Develops leadership and management skills. 1. Receives/Reviews progress and evaluates
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aims to strengthen interdisciplinary research among faculty, universities, research centers, industry partners, and government agencies to address global quantum challenges and prepare a new generation
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an in depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection
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part of an interdisciplinary research team dedicated to advancing management science, the fellows will develop novel quantitative methods at the interface of statistical learning, experimental design
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. - Contribute to the development of risk-prediction tools, biomarker panels, and precision-medicine algorithms. - Participate in NIH-funded translational studies involving spatial multi-omics, proteomics
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neurodegenerative diseases. 5. Oncomechanobiology: this area focuses on mechanobiological basis of development, stem cells, and cancer, with the aim to discover new pathways of intervention in pathological conditions
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, pharmacovigilance, pharmacoepidemiology methods development). In general you will have opportunities to learn: Understanding of pharmacovigilance workflows; GenAI based algorithm and agent development for causality