Postdoctoral Research Fellowship in BIological Informatics for FY 2006

这一行动为NSF 2006财年生物信息学博士后研究奖学金提供了资金。该奖学金支持生物学与信息科学、计算科学、数学科学和统计科学交叉的博士后水平的研究和培训。该研究金的目标是为一名青年科学家提供培训，为从事生物信息学的职业做准备，在生物信息学中将把研究和教育结合起来。对所有职业级别的生物信息学培训的需求日益增加，预计通过这些研究金培训的研究员将在培训未来的劳动力方面发挥重要作用。该研究金的研究和培训计划题为“描述和了解生态群落中个体体型分布的地理模式”。这项研究正在量化社区体型模式中大陆尺度的变异模式，并对其进行处理。它将来自三个大陆尺度数据集的个体体型分布(或尺寸谱)的数据与一套环境和生态变量相结合，以描述和理解分布的形式。培训目标包括学习制定一项研究计划，以一种既严格又广泛的科学受众的方式应用定量方法来了解生态系统。将获得的具体技能包括复杂的地理信息系统和统计建模、概率密度估计以及计算模拟和随机化技术。

This action funds an NSF Postdoctoral Research Fellowship in Biological Informatics for FY 2006. The fellowship supports research and training at the postdoctoral level at the intersection of biology and the informational, computational, mathematical, and statistical sciences. The goal of the fellowship is to provide training to a young scientist in preparation for a career in biological informatics in which research and education will be integrated. There is an increasing need for training in biological informatics at all occupational levels, and it is expected that Fellows trained through these fellowships will play important roles in training the future workforce. The research and training plan for this fellowship is entitled "Describing and understanding geographic patterns of the distribution of body sizes of individuals in ecological communities." The research is quantifying the patterns of, and processes underlying, continental-scale variability in community body size patterns. It integrates data on the distribution of body sizes of individuals (or size-spectrum) from three continental scale datasets with a suite ofenvironmental and ecological variables in order to describe and understand the form of the distribution.The training goals include learning to develop a research program that applies quantitative methods to understand ecological systems in a manner that is both rigorous and accessible to a broad scientific audience. Specific skills to be gained include sophisticated GIS and statistical modeling, probability density estimation, and computational simulation and randomization techniques.