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Program

imageGoals

The overall goal of this NRT program is to train scientists with an interdisciplinary background and conceptual framework to synthesize two divergent fields - plant science and computational/data science - and to integrate knowledge at multiple levels of biological organization. At the end of the program the trainees should be competent in the 5 areas. Detail list of areas is found here.


Contents

Our program has 5 components. All components will be open to non-trainees interested in computational plant science. Details about the components is found here.

Professional Development

Professional development preparing Trainees for a broad career path is a central component of the IMPACTS program. Trainees will participate in the following professional development activities aiming at bolstering the Trainee’s communication, leadership, management, mentoring, and teaching skills.

For more details click here.

  • Communication
  • Leadership and Management
  • Teaching
  • Mentoring
  • Career Advancement

Organization

Committee Description Members

Curriculum

Design, implement curriculum, put together course form, and work with departments/programs to clear obstacles

Dan Chitwood, Jyothi Kumar Tammy Long, Shinhan Shiu, Addie Thompson, Robert VanBuren

Evaluation

Design evaluation plan, oversee evaluation data gathering, interact with external evaluator

Jyothi Kumar Tammy Long, Shinhan Shiu

Executive committee

Work with director/co-directors on program management, review applications, delegate project report items among subcommittees

Karen Cichy, Patrick Edger, Jyothi Kumar, Tammy Long, Daniel Morris, Shinhan Shiu, Jianrong Wang, Yuying Xie

Recruitment

Interface with degree programs on advertising the NRT, attend major URM conferences in campus to recruit students

Erich Grotewold, Ning Jiang, Kevin Liu

Symposium or Retreat

Work with trainees to identify symposium topic, invited speakers, identify date, venue, and other arrangements

Trainees: Seth Hunt, Mckena Lipham

 


Reports & Logic Model