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  6. High School Students: Apply Today to Work With Machine Learning

High School Students: Apply Today to Work With Machine Learning

High school students in 10th - 12th grade are welcome to apply to work with our faculty using machine learning and image data to study biofilm and materials informatics.

  • published: 2021/04/07
  • search keywords:
  • high school
  • biofilm
The Peter Kiewit Institute from far away.

Requirements: The recruited students (10th – 12th graders) will be required to spend 8 weeks (Jun 1st - Jul 23rd) working with faculty members through regular online meetings, 20 hours a week.

Stipend: $10 per hour and 20 hours per week, for participating in the summer program

Application: The applicants should email your resume to Dr. Pei-Chi Huang, phuang@unomaha.edu, Computer Science, University of Nebraska at Omaha, by April 30th.

Overview. We will provide research experience to local high school students through the Summer High School Internship program. Students will be offered a 8-week long training program related to research focus of the project. This project will explore biofilm bacteria and material information which is a major component of the actual biomass of the Earth. We will investigate biofilm images as a form of input data to create and process visualizations of single/overlapped bacteria with an unprecedented level of detail; specifically, observes the growth and function of aggregates of cells. The research expects to provide opportunities and funding for students across a variety of fields to work together that address real-world biofilm problems using traditional machine learning approaches alongside cutting-edge data science tools/techniques.

Dr. Pei-Chi Huang will provide guidance to high school students in conducting research in machine learning to explore the biofilm and material informatics related areas as well as planning the academic pathways at the undergraduate level and beyond to carry out research in these areas. The student will learn to use machine learning tools such as Keras and Python. The project will be 8-weeks long (Jun 1st - Jul 23rd, the timeline can be flexible if needed) and the student is expected to write a 4-page report on the project experience.

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