NRT-DESE: Graduate Training in Data-Enabled Research into Human Behavior and its Cognitive and Neural Mechanisms

University Of Rochester, Rochester NY

Investigators

Abstract

Understanding the cognitive and neural basis of human behavior is one of the most fundamental areas of scientific inquiry for the 21st Century. It will impact almost every facet of human existence, including commerce, education, health care, and national security, as well as basic science. This National Science Foundation Research Traineeship (NRT) award prepares Ph.D. students at the University of Rochester to advance discoveries at the intersection of computer science, brain and cognitive sciences, and neuroscience. Trainees will be prepared to harness the burgeoning power of data science to make novel inroads into understanding the neural foundations of human behavior. Trainees will learn to be equally comfortable applying these skills in industrial and academic settings. By emphasizing both practical applications and basic science, this program will prepare trainees to develop research solutions relevant to today?s societal needs as well as develop research approaches of critical importance to future needs. Focusing on understanding the nature of intelligence, this program will provide students with skills to blend expertise in data science and computer science with a deep understanding of experimental approaches to collecting and analyzing neural and behavioral data. The program will use theories and methods from data science including machine learning and statistics to provide students with a foundation for theory development, computational modeling, and data analysis. This foundation will serve as a conceptual and methodological framework unifying their studies of artificial and biological intelligence. The hands-on, project-oriented nature of this program will provide students with the capabilities needed to conceptualize, design, and implement large-scale research projects from beginning to end. This traineeship provides a novel model for structuring interdisciplinary education, based on a modular cross-training course followed by an interdisciplinary practicum course, which can be replicated in many fields and universities.