ML Workflow

Provider(s):
University of Washington and Eastern Washington University

Description:
Students will use one of the publicly available packages for ML workflow (an example is Raven), and study the performance of different designs for an identification problem. The ML workflow will also be used for clustering physics-inspired data. One application will involve data from biomolecular strands.
The student should have access to their own computers. In the case of students from low income families, we will make every effort to provide access to a computer. A meeting with our team every two weeks is required.
This project is part of the IEEE Nanotechnology Council Summer Internship.
This is research for us as we have not tried these workflow packages. So, this will require an independent student to experiment and provide us with updates. This project may be too challenging for a student who has not used a variety of packages before.

Qualifications Required:

Previous ML experience with packages

Research Component:
This is research for us as we have not tried these workflow packages. So, this will require an independent student to experiment and provide us with updates. This project may be too challenging for a student who has not used a variety of packages before.

Location:
Remote
Hours per week:
35
Duration of internship:
8 weeks
Stipend:
None.
Start Date
June 20, 2024

Deadline for submission of application:
April 22, 2024 6:00pm

Eligibility:

High school students currently in grades 9-12 in the USA can apply.

Sorry, we cannot support international students. Please read Read Me sections in the website for more details

Important Note: Directly contacting mentors before your application is reviewed is strictly prohibited and may result in disqualification.