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STEM (teaching faculty) - Invitation to Collaborate -- Big data analysis techniques for reproducibility in life sciences

by Melanie Melendrez-Vallard 4 years ago

Hello Everyone, 

I am Melanie Melendrez-Vallard, Instructor of Biology at Anoka Ramsey Community College in Cambridge, MN.
 
I am passing along an opportunity for teaching faculty that wish to participate or collaborate in an NSF RCN-UBE grant we are currently putting together of which I am Co-PI. There are four levels of participation and one may fit your needs and interests well. See below for more information and if you are interested feel free to contact myself or Serghei directly. I hope everyone's classes wrapped up well this year and is now transitioning to a well deserved rest!
 
Happy Holidays!
Mel
 

As the Computational Education Consortium, we are preparing an NSF proposal for Research Coordination Networks in Undergraduate Biology Education (RCN-UBE) https://www.nsf.gov/pubs/2018/nsf18510/nsf18510.htm

The title of our proposal is: Computational education consortium: Big data analysis techniques for reproducibility and transparency in life sciences

The PI of this grant proposal is Serghei Mangul, a faculty at the University of Southern California interested in developing novel teaching approaches to teach data science to non-computational students. More information about my lab is available here: http://www.sergheimangul.com/

CO-PIs are (CC here): 

  • Melanie Melendrez, faculty at Anoka-Ramsey Community College

  • Keith A. Crandall, faculty at George Washington University

  • Stacey Finley, faculty at University of Southern California

  • David Koslicki, faculty at Penn State University

A one-page summary of our proposal is available here: https://docs.google.com/document/d/18-sS2aOpF8BhALVqMew3qN96lUeULvGvFWY8mmHHg4c/edit?usp=sharing

We are planning to assemble a Computational Education Consortium to teach faculties and students of the Community Colleagues how to use state-of-the-art  computational tools for big data analysis and visualization.

We hope to collaborate with you on this project.

We offer several types of participation. Please let us know which one is more suitable for you:

  1. Be part of the Steering Committee (Assessment Committee, Infrastructure Committee, Curricular Committee, Faculty Training Committee) 

  2. Be part of the External Advisory Board 

  3. Be part of Network and participate in the workshop and teaching activities 

  4. Help distribute information about planned teaching activities among faculties and students at your institution 

If you agree to participate, we would need a letter of collaboration. According to NSF rules, the letter of collaboration should be the exact text below on the official letterhead: If the proposal submitted by Dr. Mangul entitled "Computational education consortium: Big data analysis techniques for reproducibility and transparency in life sciences" is selected for funding by the NSF, it is my intent to collaborate and/or commit resources as detailed in the Project Description.

We plan to provide financial compensation for your effort.

Thanks,

Serghei (and Mel)

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Melanie Melendrez, Ph.D.
Biology Faculty
Anoka-Ramsey Community College
Cambridge, MN USA
Office: 763-433-1973
Tilly Hill 4 months, 2 weeks ago

Hello. I wanted to inquire if the program is still active? I would be interested in participating next year. My students and I discussed public health last semester. We found at https://papersowl.com/examples/public-health/ a lot of intresting. I concluded that it’s very challenging to track trends and evaluate the effectiveness of health programs without big data analysis. If possible, I’d like to learn more about how to get involved and what the requirements are.