RTG: Interdisciplinary Training in Quantitative Biological Modeling

本项目为定量生物建模跨学科研究训练基金（RTG）。博士后、研究生和本科生将获得与生物学问题相关的数学建模、数值方法和现代数据分析/统计工具的经验。学员将在跨学科的环境中进行个人研究，重点关注实验和计算生物学中当前问题的数学建模。每位学员将受益于两位导师，一位来自应用数学，另一位来自生物学科。通过围绕特定生物学主题组织的定期小组会议，学员将获得超出自己研究领域的知识和经验，西北大学以外的研究实习将拓宽学员的视野。研究生和博士后将通过与参与的教师合作创建新的课程材料来获得教学经验。作为项目的一部分，学员和本科生还将接受书面和口头交流方面的指导。该项目的一个主要目标是为应用数学专业的学生和博士后在生命科学领域的跨学科研究和他们随后的职业生涯做准备。作为该项目的一部分，研究将集中在神经科学、发育生物学、进化生物学和生态学等领域的数学模型上。模型将包含适合这些应用领域的最先进的数学、计算和统计数据分析方法。近年来，新的高通量实验技术产生了大量来自生物系统的数据，目前正在努力整合这些数据集，以了解基本的生物机制和功能。在跨学科的环境中，参与该项目的学员将分析成像、测序和其他数据，以解决紧迫的生物学问题。跨学科教师的共同指导和对学生的计划性监督，新课程的创建，以及新的垂直和同伴教学结构的发展，将极大地扩展应用数学在生物建模高影响力领域的本科生，研究生和博士后培训。这将造就新一代的数学家，他们经过交叉训练，能够适应该领域的特殊需求。该项目将进一步连接西北大学和其他研究机构的教师，加强重点领域的研究进展。

This project is an interdisciplinary Research Training Grant (RTG) on Quantitative Biological Modeling. Postdoctoral fellows, graduate students, and undergraduates will gain experience with mathematical modeling, numerical methods, and modern data analysis/statistical tools relevant to biological problems. Trainees will perform individual research in an interdisciplinary environment focusing on the mathematical modeling of current problems in experimental and computational biology. Each trainee will benefit from having two mentors, one from applied mathematics and one from a biological discipline. Trainees will gain knowledge and experience beyond that of their own research areas via regular group meetings organized around specific biological themes, and research internships outside Northwestern University will broaden trainee perspectives. Graduate students and postdoctoral fellows will gain pedagogical experience through creation of new course materials in collaboration with participating faculty. Trainees and undergraduates will also receive coaching in written and oral communication as part of the program. A major goal of this project is to expand the preparation of applied mathematics students and postdoctoral fellows for interdisciplinary research in the life sciences and for their subsequent careers. Research performed as part of this project will focus on mathematical models in fields including neuroscience, developmental biology, evolutionary biology, and ecology. Models will encompass state-of-the art mathematical, computational, and statistical data-analysis methods appropriate for these application areas. New high-throughput experimental techniques have produced a wealth of data from biological systems in recent years, and major efforts are now underway to integrate these datasets to understand fundamental biological mechanisms and functionality. Within an interdisciplinary environment, trainees participating in this project will analyze imaging, sequencing and other data to address pressing biological questions. Co-mentorships and programmatic oversight of students by interdisciplinary faculty, creation of new courses, and development of a new vertical and peer teaching structure will greatly expand undergraduate, graduate, and postdoctoral training in applied mathematics in the high impact area of biological modeling. This will lead to a new generation of mathematicians, cross-trained and attuned to the particular needs of the field. The project will further connect faculty across Northwestern University and other research institutions, strengthening research progress in the focus areas.