Postdoctoral Research Fellowship in Interdisciplinary Informatics for FY 2003

2003财年跨学科信息学博士后研究奖学金

• 批准号: 0305709
• 负责人: Kiona Ogle
• 金额: $ 10万
• 依托单位: Ogle, Kiona
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-10-01 至 2005-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0305709&HistoricalAwards=false
• 关键词: Postdoctoral; Research; Fellowship; Interdisciplinary; Informatics

Postdoctoral Research Fellowships in Interdisciplinary Informatics are sponsored jointly by the Directorates for Mathematical and Physical Sciences (MPS) and Biological Sciences (BIO) to encourage research and training that cross the traditional disciplinary boundaries between them. These fellowships provide opportunities for interdisciplinary research and educational activities in biology and informatics to a wide range of recent doctoral recipients (biologists, chemists, physicists, mathematicians, statisticians, computer scientists, and others) who seek to conduct research on biological questions using informatics tools and methods. It is expected that the Fellows trained through these fellowships will play an important role in training the future workforce. Postdoctoral training in informatics will permit junior scientists trained in biology, mathematical, chemical, and physical sciences to play key roles in developing new quantitative tools and methods that will advance informatics in biology and other fields. The research and training plan is entitled "Bayesian melding of ecological models and data: linking plant physiology and population processes." A framework is being established for linking plant physiology and population processes and uses the stochastic PHYSPOP model and Bayesian melding as a model system. A database from the NSF LTER network is being compiled, and Bayesian melding, PHYSPOP and the database combined to quantify key linkages between physiological and population quantities for a variety of species and habitats.

跨学科信息学博士后研究奖学金由数学和物理科学（MPS）和生物科学（BIO）理事会联合赞助，以鼓励跨越它们之间传统学科界限的研究和培训。这些奖学金为生物学和信息学的跨学科研究和教育活动提供了机会，以广泛的近期博士获得者（生物学家，化学家，物理学家，数学家，统计学家，计算机科学家等）寻求利用信息学工具和方法对生物学问题进行研究。预期通过这些研究金培训的研究员将在培训未来劳动力方面发挥重要作用。信息学的博士后培训将允许在生物学、数学、化学和物理科学方面受过培训的初级科学家在开发新的定量工具和方法方面发挥关键作用，这些工具和方法将推动生物学和其他领域的信息学。这项研究和培训计划的标题是“生态模型和数据的贝叶斯融合：将植物生理学和种群过程联系起来”。利用随机PHYSPOP模型和贝叶斯融合作为模型系统，建立了植物生理与种群过程联系的框架。正在编制一个来自NSF LTER网络的数据库，并将贝叶斯融合、PHYSPOP和数据库结合起来，量化各种物种和栖息地的生理数量和种群数量之间的关键联系。