RTG: Research Training in Mathematical and Computational Biology

这个RTG项目将继续发展数学和计算生物学跨学科研究和培训的综合项目，该项目位于犹他大学数学系内。训练部分将给予学生高水平的数学训练，大量接触生物学问题和技术，以及与实验生命科学家交流和合作的丰富经验。研究部分将开发和使用数学和计算方法来研究复杂的生物过程，围绕生物流体、生态学和进化生物学、神经科学和生理学四个主要研究主题组织。该项目对学生的培训将包括传统和非传统课程、期刊俱乐部、研讨会、实验室轮转、校外研究经历、研究小组会议、指导、咨询和教学经历，以及各种专业发展经历。学生将在一个高度互动的环境中接受数学家和实验家的研究指导，在这个环境中，他们将学习必要的生物学知识，并培养他们进行非传统、跨学科、前沿研究的能力。该计划将培养数学和计算生物学方面的全面整合，合作的研究人员，学者和教育工作者，从而在现代生物学的挑战性问题上承担数学的力量。由于我们的研究训练模式，许多合作研究项目将被启动，因为学生将与其他部门和机构的其他学生和教师进行交流。通过将受过定量训练的个人置于医学和生物学问题处于前沿的环境中，获得新见解和发现的可能性确实非常突出。这个项目的长期效果将是培养新一代的应用数学科学家，他们能够有效地在传统学科之间以及学术界、工业界和公共部门之间建立桥梁。

This RTG program will continue the development of a comprehensive program of cross-disciplinary research and training in Mathematical and Computational Biology, housed within the Department of Mathematics at the University of Utah. The training component will give students a high level of mathematical training, substantial exposure to biological problems and techniques, and extensive experience in communication and collaboration with experimental life scientists. The research component will develop and use mathematical and computational methods to study complex biological processes, organized around four major research themes of biofluids, ecology and evolutionary biology, neuroscience and physiology. The training of students in this program will include traditional and non-traditional coursework, journal clubs, seminars, laboratory rotations, extramural research experiences, research group meetings, mentoring, consulting and teaching experiences, as well as a variety of professional development experiences. Students will receive research mentoring by mathematicians and experimentalists in a highly interactive setting in which they learn the necessary biology and develop the ability to do non-traditional, cross-disciplinary, cutting edge research. This program will train fully integrated, collaborative researchers, scholars and educators in mathematical and computational biology, thus bringing to bear the power of mathematics on the challenging problems of modern biology. Many collaborative research projects will be initiated as a result of our research training paradigm, as students become engaged with other students and faculty in other departments and institutions. By placing quantitatively trained individuals in an environment where medical and biological problems are at the forefront, the possibilities for new insights and discoveries are truly outstanding. The long term effect of this program will be a new generation of applied mathematical scientists who can work effectively to build bridges between traditional disciplines and among academia, industry and the public sector.