A ten-week paid fellowship beginning in early June at Los Alamos National Laboratory, aimed at graduate students and advanced undergraduates who want to integrate machine learning into their research careers. Fellows are mentored by LANL machine learning researchers, work on real scientific problems using high-performance computing, attend seminars from Laboratory and external researchers, and aim to produce peer-reviewed publications as co-authors. Applicants must be enrolled in or accepted to an undergraduate or graduate degree programme with a cumulative GPA of at least 3.2 and be able to live and work in the United States; a background in probability, statistics, algorithms or statistical learning is recommended. The fellowship covers both stipend and travel.