Genetic Mechanisms and Evolution
遗传机制和进化
基本信息
- 批准号:10427128
- 负责人:
- 金额:$ 83.26万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-07-01 至 2026-06-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Recent technological advances have transformed genetics research, and social changes have caused major
shifts in best practices for graduate education, research training, and mentoring. We propose an innovative
interdisciplinary predoctoral T32 program, Genetic Mechanisms and Evolution (GME), which is specifically
crafted to meet the challenges and opportunities presented by these changes. The GME program will train a
diverse group of world-class Ph.D. scientists in molecular, statistical, and evolutionary genetics
research who will serve as the next generation of innovative scientific leaders in genetics. Training will
ensure development of multidisciplinary competence across these fields, with a strong foundation in
quantitative and computational analysis for every student.
The GME training program leverages the world-class strength of the University of Chicago in genetics.
Mentors include 56 faculty with extraordinary records of research and graduate training, drawn from 14
departments across the fields of evolutionary, statistical, and molecular genetics. Further, the University’s
unique organizational structure brings all areas of genetics into a single division and makes possible the
interdisciplinary program we propose. Trainees for 18 funded positions will be selectively drawn from 9
graduate programs across disciplinary areas. The pool of potential trainees is extraordinarily well-qualified and
diverse (49% women and 26% URM over the last 5 years).
Trainees will be funded in years 2-3 of their studies, but they will participate in training and advising
activities from matriculation through graduation. A new interdisciplinary core course and breadth requirements
will develop student foundations in molecular, statistical, and evolutionary genetics and build strong skills in
programming and statistics. Specialized workshops and an annual hackathon will provide further rigorous
training in computational and quantitative analysis of modern genetic data. Formal writing instruction along with
workshops in grant-writing and oral presentation skills will train scientists for effective communication and help
ameliorate disparities in preparation among students from diverse backgrounds. Individual development plans,
mentor-mentee contracts, faculty mentor training, and peer mentoring will facilitate trainee success and allow
growth of a mutually supportive community of faculty and students. Participation in a pioneering career
development program will support trainees in finding and preparing for a variety of post-PhD career paths.
Recruitment and retention of an increasingly diverse group of students will be further strengthened by
participating in pipeline and outreach programs, bridge activities for new students, and faculty training to
enhance the inclusivity of the training environment and admissions process. All these activities -- building on
the strengths of an exceptional cadre of trainees, trainers and institutional support – will allow us to recruit and
train the future leaders of 21st century genetics research.
最近的技术进步改变了遗传学研究,社会变化导致了重大的
研究生教育、研究培训和指导方面的最佳实践的转变。我们提出了一种创新的
跨学科博士前T32计划,遗传机制和进化(GME),具体是
为迎接这些变化带来的挑战和机遇而精心设计。GME计划将培训一名
世界一流的分子、统计学和进化遗传学博士科学家组成的多元化群体
谁将成为遗传学领域的下一代创新科学领袖。培训将会
确保在这些领域发展多学科能力,具有坚实的基础
为每个学生提供定量和计算分析。
GME培训计划利用了芝加哥大学在遗传学方面的世界级实力。
导师包括56名在研究和研究生培训方面有非凡记录的教职员工,他们来自14名
在进化、统计学和分子遗传学领域的各个系。此外,该大学的
独特的组织结构将遗传学的所有领域归入一个单一的部门,使
我们提出了跨学科的计划。18个资助职位的实习生将从9个
跨学科领域的研究生课程。潜在的实习生队伍非常合格,而且
多样化(49%的女性和26%的女性在过去5年中)。
学员将在学习的2-3年内获得资助,但他们将参加培训和咨询
从入学到毕业的所有活动。新的跨学科核心课程和广度要求
将培养学生在分子、统计学和进化遗传学方面的基础,并建立强大的技能
编程和统计。专业研讨会和一年一度的黑客马拉松将提供更严格的
培训现代遗传数据的计算和定量分析。正式的写作指导以及
赠款撰写和口头陈述技巧的研讨会将培训科学家进行有效的沟通和帮助
改善来自不同背景的学生在准备工作方面的差距。个人发展计划,
导师-学员合同、教师导师培训和同伴指导将促进学员的成功并允许
教职员工和学生相互支持的社区的成长。参与创业型职业
发展计划将支持学员寻找并为各种博士后职业道路做准备。
将进一步加强对日益多样化的学生群体的招聘和留住
参与管道和外展计划,为新生搭建桥梁活动,以及培训教师以
增强培训环境和招生过程的包容性。所有这些活动--建立在
一支优秀的实习生、培训员和机构支持队伍的力量-将使我们能够招募和
培养21世纪遗传学研究的未来领导者。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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John Novembre其他文献
John Novembre的其他文献
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{{ truncateString('John Novembre', 18)}}的其他基金
Theory, Methods, and Resources for Understanding and Leveraging Spatial Variation in Population Genetic Data
理解和利用群体遗传数据空间变异的理论、方法和资源
- 批准号:
10623985 - 财政年份:2023
- 资助金额:
$ 83.26万 - 项目类别:
Extending Tools for Visualization of Geographic Structure in Population Genomic Data
群体基因组数据中地理结构可视化的扩展工具
- 批准号:
9904741 - 财政年份:2019
- 资助金额:
$ 83.26万 - 项目类别:
Extending Tools for Visualization of Geographic Structure in Population Genomic Data
群体基因组数据中地理结构可视化的扩展工具
- 批准号:
10426037 - 财政年份:2019
- 资助金额:
$ 83.26万 - 项目类别:
Haplotype-based analysis methods for population genomics
基于单体型的群体基因组分析方法
- 批准号:
8601543 - 财政年份:2013
- 资助金额:
$ 83.26万 - 项目类别:
Haplotype-based analysis methods for population genomics
基于单体型的群体基因组分析方法
- 批准号:
9000730 - 财政年份:2013
- 资助金额:
$ 83.26万 - 项目类别:
Haplotype-based analysis methods for population genomics
基于单体型的群体基因组分析方法
- 批准号:
8788051 - 财政年份:2013
- 资助金额:
$ 83.26万 - 项目类别:
Haplotype-based analysis methods for population genomics
基于单体型的群体基因组分析方法
- 批准号:
8670447 - 财政年份:2013
- 资助金额:
$ 83.26万 - 项目类别:
Haplotype-based analysis methods for population genomics
基于单体型的群体基因组分析方法
- 批准号:
9198031 - 财政年份:2013
- 资助金额:
$ 83.26万 - 项目类别:
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