权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Neuro-physical-computational Sciences Graduate Training(RMI)

神经物理计算科学研究生培训（RMI）

基本信息

批准号：
7483049
负责人：
TIMOTHY J EBNER
金额：
$ 7.16万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-09-30 至 2010-07-31
项目状态：
已结题

项目摘要

The proposed interdisciplinary training program at the University of Minnesota combines graduate training in the computational, chemical, physical, and engineering sciences with graduate training in neuroscience. Neuroscience is a highly interdisciplinary field that uses a variety of experimental approaches to understand the development, structure, and function of the nervous system. As neuroscience matures, the need grows for quantitative modeling, physical and chemical insights, advanced technologies, and state-of-the-art hardware and software that the computational, chemical, physical and engineering sciences can provide. Therefore, interdisciplinary graduate training is needed to take the maximum advantage of these opportunities. The proposal incorporates the strengths, resources, and administrative structures of several existing graduate programs and the University of Minnesota Supercomputing Institute with an interdisciplinary faculty with diverse research interests, to provide a new paradigm in graduate education. We propose to offer 5 three-year Fellowships each year to attract outstanding pre-doctoral students. Enrolling in existing degree programs in Biomedical Engineering, Chemistry, Computer Science, Mathematics, Neuroscience, Physics and Scientific Computation. The Fellows will be trained across disciplines using a variety of tools including special interdisciplinary coursework, research rotations, dual thesis advisors, special seminars and symposia and unique training opportunities. Each trainee's thesis work will cross the disciplines of neuroscience and the physical/computational sciences. An advisory system will help guide students through the program. Also, several mechanisms are proposed to evaluate the effectiveness of the training program. The trainees will receive instructions in the responsible conduct of research. The proposal documents the efforts that the training program and University will make to ensure that traditionally underrepresented students are recruited and included in the program. On completion the trainees will be prepared for research careers in academia, industry and government. The overall goal is to train the next generation of scientists who can bridge the gap between biology and the physical/computational sciences. Broader impacts include advancing our understanding of the brain, cross-fertilization of the disciplines, and establishing a new model for interdisciplinary graduate training.

明尼苏达大学拟议的跨学科培训计划将计算、化学、物理和工程科学的研究生培训与神经科学的研究生培训结合起来。神经科学是一个高度交叉的领域，它使用各种实验方法来了解神经系统的发展、结构和功能。随着神经科学的成熟，对定量建模、物理和计算、化学、物理和工程科学可以提供的化学见解、先进技术和最先进的硬件和软件。因此，需要进行跨学科的毕业生培训，以最大限度地利用这些机会。该提案结合了优势、资源和管理几个现有研究生课程的结构和明尼苏达大学超级计算研究所拥有具有不同研究兴趣的跨学科教员，以提供研究生教育的新范式。我们建议每年提供5个为期三年的奖学金，以吸引优秀的博士生。注册现有的生物医学工程、化学、计算机科学、数学、神经科学、物理和科学计算学位课程。研究员将使用各种工具进行跨学科培训，包括特殊的跨学科课程、研究轮换、双重论文顾问、特别研讨会和专题讨论会以及独特的培训机会。每个学员的论文工作将跨越神经科学和物理/计算科学的学科。一个咨询系统将帮助指导学生完成该项目。此外，还提出了几种机制来评估培训计划的有效性。受训者将接受负责任地进行研究的指导。提案记录了培训计划和大学将做出的努力确保传统上代表性不足的学生被录取并纳入该计划。完成培训后，学员将为在学术界、工业界和政府部门从事研究工作做好准备。总体目标是培养能够弥合生物学和物理/计算科学之间差距的下一代科学家。更广泛的影响包括促进我们对大脑的理解，学科之间的交叉受精，以及建立跨学科研究生培养的新模式。