Interdisciplinary Training in Computational Neuroscience

项目摘要 基本原理：为了了解大脑的许多疾病，有必要解决其复杂性。 越来越大和复杂的数据集正在收集，但用于分析和建模的工具， 数据尚未提供。迫切需要更多受过计算神经科学训练的研究人员。 该项目支持计算神经科学（TPCN）的跨学科研究生培训计划， 卡内基梅隆大学（CMU）和匹兹堡大学（皮特），以及一个暑期学校， 计算神经科学的本科生，这是提供给学生来自大学和 美国各地的大学。 卡内基梅隆大学（CMU）是定量领域的世界领导者和创新者， 机器学习，计算机科学和人工智能，最近，神经科学已经成为一个新兴的领域。 在大学的战略增长领域。匹兹堡大学以其临床实力而闻名。 和生物医学研究项目。TPCN设置在一个高度合议，跨学科的环境中， 我们的认知神经基础中心（CNBC），由CMU和皮特共同运营。CNBC的 成立于1994年，旨在促进对大脑功能神经机制的跨学科研究， 现有162名教职员，分布于32个学系。 目标：TPCN的目标是： 1)支持神经科学博士生的计算培训， 2)通过扩大现有的 硕士到博士培训计划，为他们接受计算领域的高级研究生培训做好准备 神经科学， 3)通过正式的学术辅修课程扩大本科生的计算培训， 计算神经科学， 4)支持本科生暑期课程，结合为期两周的“训练营”概述， 有8周研究经验的计算神经科学， 5)创建在线材料，不仅为我们自己的学生，但在网上公开， 6)通过我们与少数民族服务机构建立的关系加强我们的招聘工作。

Project Summary Rationale: To understand the many disorders of the brain it is necessary to grapple with its complexity. Increasingly large and complicated data sets are being collected, but the tools for analyzing and modeling the data are not yet available. More researchers trained in computational neuroscience are desperately needed. This project supports interdisciplinary graduate training programs in computational neuroscience (TPCN) at both Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), and a summer school in computational neuroscience for undergraduates, which are available to students coming from colleges and universities throughout the United States. Carnegie Mellon University (CMU) is a world leader and innovator in quantitative fields such as machine learning, computer science, and artificial intelligence, and recently, neuroscience has emerged as a field for strategic growth at the university. The University of Pittsburgh is renowned for the strength of its clinical and biomedical research programs. The TPCN is set within a highly collegial, cross-disciplinary environment of our Center for the Neural Basis of Cognition (CNBC), which is operated jointly by CMU and Pitt. The CNBC was established in 1994 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 162 faculty having appointments in 32 departments. Goals: The goals of the TPCN are to: 1) Support computational training of PhD students across the neurosciences, 2) Broaden accessibility for students historically underrepresented in STEM by augmenting an existing MS-to-PhD training program that prepares them for advanced graduate training in computational neuroscience, 3) Expand computational training of undergraduate students through a formal academic minor in computational neuroscience, 4) Support an undergraduate summer program that combines a two-week “boot-camp” overview of computational neuroscience with an 8-week research experience, 5) Create online materials that not only serve our own students but are publicly available on the web, and 6) Enhance our recruitment through relationships we have developed with minority-serving institutions.