Computational Medicine in the Heart, Integrated Training Program

项目摘要 心血管疾病是世界范围内发病率和死亡率上升的原因。的确有 令人兴奋的是，计算医学，一个结合工程学科和生活的新兴领域 科学，将使科学和临床取得突破，并加快从病床到床边的转换。 然而，这一领域的培训项目很少，因此学员经常临时学习。 我们为心脏计算医学的一个新的多学科T32项目寻求资金： 斯坦福大学的综合培训计划(CHIP)。CHIP将为3名博士后、医学博士或 -医学博士/博士研究生每年，每人在工程学交叉路口接受两年的培训，简历 生理学和医学。受训者将从事由教师指导的尖端研究项目 工程和生命科学方面的互补专业知识，并选择教学课程来积累专业知识， 专业成长，发展社区。芯片的前瞻性愿景解决了以下关键优先事项 几个国家机构，填补了目前跨学科培训方面的空白。 斯坦福CHIP利用一流工程、医学和工程学院的师资和资源 人文与科学。T32由一位内科工程师和一位工程师生理学家共同指导， 吸引了来自13个系和科室的38名教职员工，重点是妇女和以下- 代表少数族裔。关键支持由跨学科心血管研究所(CVI)和 斯坦福大学计算与数学工程研究所(ICME)。教职员工将为学员提供 从细胞到器官、从工作台到床边的心血管科学研究机会，以及计算 科学、临床护理和治疗创新。教职员工高度合作，拥有出众的 引导受训人员进入独立的科学职业生涯的记录。 申请者的选择和方案的所有方面都强调纳入任职人数不足的受训人员 组。受训人员不需要同时具有工程学和生命科学背景。T32将 为工程师提供定制的简历科学教学，为生命科学研究员提供工程学教学，并提供高级交叉课程 每个人都有纪律问题。核心教育学还包括伦理，负责任的科学行为，方法 确保重现性。对于学员和教职员工来说，多样性、公平和包容性是核心。评估将是 实习生和教职员工之间的建设性和双向。 总而言之，斯坦福大学的芯片T32为博士研究生、博士研究生和博士研究生提供 在生物工程、简历科学和医学的交汇处接受世界级的培训。T32的定位很好 由于将这些顶级资源并置在硅谷的一个园区内而获得成功，硅谷是 数据科学、人工智能和治疗方面的创新。我们的抱负目标是CHIP毕业 将成为工程学、生理学和医学领域的全球科学领先者。

Project Summary Cardiovascular (CV) diseases are rising causes of morbidity and mortality worldwide. There is excitement that computational medicine, an emerging field combining engineering disciplines with the life sciences, will enable scientific and clinical breakthroughs and accelerate bench-to-bedside translation. However, few training programs exist in this field, and so trainees often learn ad hoc. We seek funding for a new multidisciplinary T32 program in Computational medicine in the Heart: Integrated training Program (CHIP) at Stanford. CHIP will provide cutting-edge training for 3 post-PhD, -MD or -MD/PhD fellows annually, each undergoing 2 years of training at the intersection of engineering, CV physiology and medicine. Trainees will pursue a cutting-edge research project mentored by faculty with complementary expertise in engineering and the life sciences, and select didactic courses to build expertise, grow professionally, and develop community. The forward-looking vision of CHIP addresses key priorities of several National Agencies and fills current gaps in interdisciplinary training. Stanford CHIP leverages faculty and resources at top-ranked Schools of Engineering, Medicine and Humanities and Sciences. The T32 is co-directed by a physician-engineer and an engineer-physiologist, bringing 38 faculty from 13 Departments and Divisions with strong emphasis on women and under - represented minorities. Key support is provided by the inter-disciplinary Cardiovascular Institute (CVI) and the Institute for Computational and Mathematical Engineering (ICME) at Stanford. Faculty will provide trainees with research opportunities in CV science spanning cell-to-organ and bench-to-bedside, as well as computational science, clinical care, and therapeutic innovation. The faculty are highly collaborative and have exceptional track records of launching trainees into independent scientific careers. Applicant selection and all aspects of the program stress inclusion of trainees from under-represented groups. Trainees will not be required to have backgrounds in both engineering and life sciences. The T32 will provide tailored teaching of CV science to engineers, engineering to life-science fellows, and advanced cross- disciplinary topics to each. Core didactics also include ethics, the responsible conduct of science, methods to ensure reproducibility. Diversity, equity and inclusion are central for trainees and faculty. Evaluation will be both constructive and bidirectional between trainees and faculty. In summary, the CHIP T32 at Stanford provides post-MD, post-PhD and post-MD/PhD graduates with world-class training at the intersection of bioengineering, CV science and medicine. The T32 is well positioned for success due to the co-location of these top-tier resources on a single campus in Silicon Valley, a hub of innovation in data science, artificial intelligence and therapy. Our aspirational goal is that CHIP graduates will become global scientific leaders at the cusp of engineering, physiology and medicine.