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Cross-Disciplinary Neural Engineering (CDNE) Training Program

Cross-Disciplinary Neural Engineering (CDNE) Training Program
跨学科神经工程(CDNE)培训计划
批准号:
10205622
负责人:
BRUCE J GLUCKMAN
金额:
$13.55万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-07-01 至 2026-06-30

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Project Summary The Cross-Disciplinary Neural Engineering (CDNE) predoctoral training program will train the future research leaders able to bridge across the disciplinary boundaries of engineering, sciences and mathematics to neurosciences and the treatment of human brain health. Such leaders are necessary to produce lasting and relevant engineering, scientific and medical findings that will lead to improved human health. The CDNE program build from the strengths of the affiliated graduate programs and Penn State’s Center for Neural Engineering to create a new training program focused on cross- disciplinary training for graduate students. Trainees coming from a range of disciplinary programs including engineering, physics, mathematics and neuroscience graduate programs will complete a common neuroscience course core; be co-mentored by at least two trainers across disciplinary realms of Materials and Devices, Theory and Computation, Brain Physiology, and Human Brain Health; and participate in a range of activities designed to enhance cross disciplinary communication and collaboration, quantitative approaches, and scientific rigor. The CDNE will augment existing graduate programs in Engineering Science and Mechanics, Mechanical Engineering, Electrical Engineering, Mathematics, Physics, Anthropology, Neuroscience, and Biomedical Engineering, to provide specialized training in neural engineering. The CDNE program will fund the training of a total of 15 graduate students during the five years by a combination the NIH (10) and PSU (5) funded fellowships. Each trainee will be supported for a two-year period starting in their 3rd year. Trainees will gain experience working across disciplines and able to be both experts in one domain, and able to understand the language, science needs of other domains and thereby make significant contributions bridging across both.
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