Neuro-physical-computational Sciences Graduate Training(RMI)

描述（由申请人提供）： 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相结合。神经科学是一个高度跨学科的领域，使用各种实验方法来了解神经系统的发育，结构和功能。随着神经科学的成熟，对定量建模，物理和化学见解，先进技术以及计算，化学，物理和工程科学可以提供的最先进的硬件和软件的需求也在增长。因此，需要跨学科的研究生培训，以最大限度地利用这些机会。该提案结合了现有的几个研究生课程和明尼苏达大学超级计算研究所的优势，资源和行政结构，具有不同研究兴趣的跨学科教师，为研究生教育提供了一个新的范式。 我们建议每年提供5个为期三年的奖学金，以吸引优秀的博士前学生：在生物医学工程，化学，计算机科学，数学，神经科学，物理学和科学计算现有的学位课程入学。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，双论文顾问，特殊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计划。此外，提出了几种机制来评估培训计划的有效性。受训人员将接受负责任地进行研究的指导。该提案记录了培训计划和大学将做出的努力，以确保传统上代表性不足的学生被招募并纳入该计划。完成后，学员将准备在学术界，工业界和政府的研究生涯。 总体目标是培养下一代科学家，他们可以弥合生物学和物理/计算科学之间的差距。更广泛的影响包括推进我们对大脑的理解，学科的交叉，以及建立跨学科研究生培养的新模式。

DESCRIPTION (provided by applicant): 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.