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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
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. These efforts cover more than just medicines. Research Project: The aim of this research focuses on integrating FDA’s GenAI tool’s capabilities (through API calls) into the InfoViP platform while developing
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. Research Project: The project involves using FDA’s AI tool ‘Elsa,’ which uses either Claude Sonnet or Gemini models, to develop prompts to summarize different industry submissions and validate outputs
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storage physiology, abiotic stress resilience, flavor and nutritional quality; and development of molecular tools, pest management and plant breeding strategies. Research Project: This appointment is
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literature and no clinical pharmacology guidance exists due to their novelty and rapid evolution. The research aims to facilitate product development, assist review decision-making, identify regulatory
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conducts regulatory science and research activities based on quantitative approaches. Some of the responsibilities residing in DQMM include providing quantitative method support for guidance development
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permeability assays and imaging-based analyses); 3) Analytical method development using fluorescence microscopy, ELISA, and LC–MS for drug quantification; 4) Data management and interpretation workshops
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to join a collaborative project with interdisciplinary research that focuses on developing mesenchymal stromal cell-derived extracellular vesicles (MSC-EVs) as a novel therapeutic approach for systemic
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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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the performance characteristics of existing MedDRA search strategies and a novel search strategy. You will collaborate with the research team to interpret findings and develop materials to disseminate best