课题基金 / 基金详情

项目摘要

项目成果

Joel G Pounds的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
PROJECT SUMMARY (See instructions): The overall purpose of the Admlnistrafive Core is to ensure scientific, organizational and operational excellence ofthe Program and its ability to meet scientific milestones and objectives ofthe NIEHS. The Core will be responsible for overall organizational structure, administrative activities and fiscal responsibilities of the PNNL's Program for the Toxicity of Engineered Nanoniaterials, and will ensure all research is conducted with integrity and with appropriate environmental, safety and health considerations and planning. These responsibilities will be accomplished by the following Aims: 1) Provide a management and admlnistrative support structure for decision-making processes, planning of research activities, and efficient management of program funds, and resource allocation with the Program; 2) Promote cross-disciplinary interactions and coordination among the research projects and the research core within the Program, including material synthesis and materials characterization; 3) Coordinate statistical analysis and modeling of experimental data across research projects and the research core within the Program; and 4) Ensure effecfive liaison with NIEHS and the broader NIEHS nanotoxicology research consortium. The Admlnistrafive Core will also provide oversight and prioritization of biostatistical resources and activities needed for data integration across projects, biological systems, and to maintain focus of the overall Program goals of developing novel approaches for hazard identificafion and risk assessment for engineered nanomaterials.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Project 2: Role of ENP Physicochemical Properties on Biokinetics and Response in
Integrating Structive Activity, Biokinetics and Response for ENP Risk Assessment
Integrating Structive Activity, Biokinetics and Response for ENP Risk Assessment
Integrating Structive Activity, Biokinetics and Response for ENP Risk Assessment
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis