Tri-Institutional PhD Program in Computational Biology and Medicine

项目总结/摘要 计算生物学和医学（CBM）的三机构培训计划利用 康奈尔大学在伊萨卡，纽约州，威尔康奈尔大学的杰出的教育和研究资源， 纽约市医学院和纪念斯隆凯特琳癌症中心的研究项目 在纽约市培训计算生物学家的方法，他们需要解决复杂的 跨学科的生物医学问题。建立信任措施方案的特点是： ·定量和生物科学课程; ·研究轮换，使一个明智的论文选题; ·指导论文研究在一个不同的阵列的基础转化实验室; ·培训生研究进展研讨会系列，以提高计划的凝聚力，培养流利的 相关学科，并提供科学演示实践的机会; ·培训和指导进行严格和可复制的科学研究; ·一系列有计划的丰富活动，包括每年的场外务虚会，学生 介绍他们的工作，并会见校友，午餐与来访的研讨会发言人，奖学金和 手稿写作培训，以及RCR和可复制研究实践的年度更新; ·通过与项目共同主任的年度正式会议（一年两次）提供积极的指导和辅导 论文委员会会议，包括职业讨论和年度IDP; ·接触各种职业道路，以成功过渡到生物医学研究队伍。 该方案已成立16年，其培训成功的记录不断扩大， 包括及时毕业和将毕业生安置在研究相关职业的良好记录， 在学术界之外。在此建议中，我们要求8个T32插槽（相比之下，我们的 前T32），这是很有道理的高素质的培训补助金合格申请人的深池， 大量的尖端论文研究机会与领先的教师科学家，和培训 丰富是固有的增加临界质量的学生。 要求的T32资金将大大有助于建立信任措施方案继续实现其使命， 卓越的培养多样化的下一代科学家，严格和可重复的发展， 应用计算和分析方法来解决生物学和医学中的复杂问题， 准备他们的研究相关的学术和非学术职业后，及时完成其 博士学位。

Project Summary/Abstract The Tri-Institutional Training Program in Computational Biology and Medicine (CBM) takes advantage of the outstanding educational and research resources of Cornell University in Ithaca, NY, the Weill Cornell Medical College in New York City, and the research programs of Memorial Sloan Kettering Cancer Center in New York City to train computational biologists in the approaches they need to solve complex interdisciplinary biomedical problems. The CBM Program is characterized by: • coursework in both quantitative and biological sciences; • research rotations to enable a well-informed thesis topic selection; • mentored thesis research in one of a diverse array of basic to translational laboratories; • trainee Research-in-Progress seminar series to enhance program cohesion, foster fluency in relevant disciplines, and provide opportunities for scientific presentation practice; • training and mentorship in performing rigorous and reproducible scientific research; • an array of programmatic enrichment activities, including an annual offsite retreat at which students present their work and meet alumni, lunches with visiting seminar speakers, fellowship and manuscript writing training, and annual refreshers in RCR and reproducible research practices; • active guidance and mentoring via annual formal meetings with program co-Directors, biannual thesis committee meetings that include career discussions, and annual IDPs; • exposure to various career paths for successful transition into the biomedical research workforce. The Program, which is well established in its 16th year, has an expanding record of training success, including timely graduation and a strong record of placing graduates in research-related careers both in and outside academia. With this proposal, we are requesting 8 T32 slots (compared to 9 slots in our previous T32), which is well justified by the deep pool of highly qualified training-grant eligible applicants, large array of cutting-edge thesis research opportunities with leading faculty scientists, and the training enrichment that is inherent to an increased critical mass of students. The requested T32 funding would greatly aid the CBM program in continuing to achieve its mission of excellence in training a diverse next generation of scientists to rigorously and reproducibly develop and apply computational and analytical methods to solve complex problems in biology and medicine and to prepare them for research-related academic and non-academic careers following timely completion of their PhD degrees.