Postdoc: Design and Application of Parallel Computational Algorithms for Hydrodynamic Steering

Kim 9504286这项提议的目标是在粘性流体中识别物体的形状，因为它是许多重要的物理化学和生物过程的重要属性。例如，从在硅衬底上流体自组装砷化镓器件，到在实施从氨基酸组装蛋白质的遗传密码过程中蛋白质与DNA的相互作用。该项目为申请者提供了极好的机会，通过严格计算支配结构-功能关系的物理力，补充以前在蛋白质化学、酶学和结构-功能分析方面的实验室培训。培训计划将从简单的几何形状开始，然后以布鲁克海文蛋白质数据库中存档的复杂几何形状结束。

Kim 9504286 The objective of this proposal is to shape recognition between objects in a viscous fluid as it is an important attribute of many important physicochemical and biological processes. Examples range from fluidic self-assembly of GaAs devices on Silicon substrate, to protein-DNA interactions during the implementation of the genetic code for assembly of proteins from amino acids. This project offers the applicant outstanding opportunities to complement previous laboratory training in protein chemistry, enzymology, and structure-function analysis, through rigorous computation of physical forces governing structure-function relationships. The training program will examine hydrodynamic steering starting from the simpler geometries, then end with the complex geometries as archived in the Brookhaven Protein Databank.