Los Alamos National LaboratoryInformation Science and Technology Institute (ISTI)
Implementing and fostering collaborative research, workforce and program development, and technical exchange

Applied Machine Learning Summer Research Fellowship

Creating Next-Generation Leaders in Machine Learning.

Contacts  

  • Program Lead
  • Natalie Klein
  • Program Co-Lead
  • Nick Lubbers
  • Program Co-Lead
  • Yen Ting Lin
  • Program Co-Lead
  • Jon Schwenk
  • Administrative Assistant
  • Iris Eguino

School Inquiries  

Applications are open for AML 2024! Please click here for the 2024 project descriptions and application form.

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The Applied Machine Learning Summer Research Fellowship is an intense 10-week program aimed at providing graduate students with a solid foundation in modern machine learning through applications of importance to the National Lab and the world. Projects include developing methodologies to address practical use of machine learning including scalability, transparency, robustness and extensibility. This is a paid fellowship that includes reimbursement for travel expenses.

The program is sponsored by the Information Science and Technology Institute (ISTI) and the Center for Nonlinear Studies (CNLS).

Description

Research Fellows will learn hands-on by engaging in scientific research using machine learning. Research will be guided by mentors with machine learning, scientific, and computational expertise.

See list of projects with descriptions.

Students will work on high performance computing clusters, apply practical and state-of-the-art ML tools, and gain experience in communicating their work through discussions and presentations. Students will attend seminars by LANL researchers and external visitors. We aim for high-impact summer projects that will lead to peer-reviewed, co-authored publications.

Students

This multidisciplinary program is designed for graduate and upper-level undergraduate students from all science, math, computer science, and technology fields who are seeking to incorporate machine learning into their research careers. As a general guideline, students should have a background in one of the following: probability theory, statistical methods, algorithms, or statistical learning. Experience with programming and machine learning packages is encouraged. Specific skills needed for each project are listed in the project descriptions and the application form asks which projects you are most interested in.

Application

To apply, you will need to submit the following materials:

  • Letter of intent stating strengths, goals, interests, and how the AML fellowship will help you achieve your goals. We strongly encourage applicants to review the project descriptions and elaborate on the alignment of the applicant’ skills, experience, and professional development to the selected projects. There is no specific formatting or length requirement, but a good letter of intent is usually approximately one page in length.
  • Current resume / CV
  • Unofficial university transcripts (official transcripts will be required if a position is offered and accepted); please make sure the transcripts do not contain your social security number, birthday, or other personally identifiable information
  • Letter of recommendation from a faculty member

Duration & Location

The 2024 program has a start date of May 28, 2024, and lasts for 10 weeks. (Some flexibility on precise start and end dates may be afforded for extenuating circumstances). AML will take place as an on-site program at LANL, rather than the virtual internship format that was used in recent years.

Eligibility Requirements

  • Must be accepted to or enrolled in a graduate degree program
  • Must have and maintain a cumulative G.P.A. of 3.2/4.0 or better
  • Must be available to live and work in the United States.

Questions?

More information about jobs and careers at Los Alamos. Or, take a look at other ISTI summer programs for students.

See our FAQs page, or if your question isn’t covered, you can contact us.