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

Creates next-generation leaders in Machine Learning for Scientific Applications

September 13, 2017
AML Group

Contacts  

  • Professional Staff Assistant
  • Nickole Aguilar Garcia
  • (505) 665-3048
  • Email

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. Projects include developing methodologies to address practical use of machine learning including scalability, transparency, robustness and extendibility. Projects will apply machine learning to problems in hyperspectral imagery, event forecasting, and text mining; as well as problems in geosciences such as flow dynamics in fracture networks, geysers, and the atmosphere; seismic signal analysis, and particle acceleration. This is a paid fellowship.

The program is sponsored by the Information Science and Technology Institute (ISTI) and the Center for Space and Earth Sciences (CSES).

Description

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

See list of projects with descriptions.

Students will work on high performance computing clusters, apply practical ML tools, and gain experience in communicating their work through posters and oral 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 multi-disciplinary program is designed for graduate students from all STEM 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.

To apply, submit:

  • Letter of intent stating strengths, goals, interests, and how the AML fellowship will help you achieve your goals
  • Current resume / CV
  • Unofficial university transcripts (official transcripts will be required if position offered and accepted)
  • Letter of recommendation from a faculty member

Apply here.

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Duration & Location

The program will be 10 weeks long from May 29 through August 3, 2018, and will be held at Los Alamos National Laboratory. (Some flexibility on these dates is possible for extenuating circumstances).

Each student selected for a fellowship will receive a stipend in the range of $10,000 to $13,700 depending on number of graduate credit hours completed.

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 

Students must be available to live and work in Los Alamos, New Mexico.

Applications must be submitted by December 15, 2017 for the first round of consideration. Late applications may also be submitted until January 15, 2018.

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