Data Science Summer Institute Undergraduate Student Internship

Laboratory, Performance, Computer, Python, Matlab, Simulation, Security
Full Time

Job Description

Company Description
Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are looking for individuals that demonstrate an understanding of working in partnership with team peers, who engage, advocate, and contribute to building an inclusive culture, and provide expertise to solve challenging problems.
Job Description
We have multiple openings for our Undergraduate summer internship program in data science. Our openings are for undergraduate level students to join the Data Science Summer Institute (DSSI). The DSSI is a 12-week summer internship program and selected interns will be given the opportunity to engage in practical research to further their educational goals. The selected interns will work in the data science field and provide technical and/or research support to projects in the area of Machine Learning, Statistics, High Performance Computing, and other related fields.

In this roleyou will:
  • Work with scientists, engineers and technical staff members to provide technical and/or research support to projects in the areas of computational science, numerical methods, mathematics, or other related fields.
  • Under close supervision, will participate in research in assigned area.
  • Gather and analyze data and information in support of scientific research.
  • Attend data science related short course, meetings, and participate in a data science challenge.
  • Participate in research planning and evaluation discussion.
  • Attend relevant seminars and participate in DSSI related courses, meetings and events.
  • Present one seminar or poster on your research project.
  • Perform other duties as assigned.
  • Must be a continuing college or university student in good standing at an accredited institution pursuing an undergraduate degree in Computer Science, Statistics, Mathematics, Machine Learning, Computer Vision, Bioengineering, or other related fields.
  • Effective programming skills in a high-level language such as R, Python or Matlab. Ability to apply basic principles of data sciences (machine learning, statistics, computer science, mathematics) to solve technical problems.
  • Ability to present and communicate concepts and ideas.
  • Ability to work in a team environment.
  • Effective communication skills.
  • Desire to understand and explore why certain algorithms are well-suited to specific applications.
  • Desire to participate in individual or team efforts including the LLNL DSSI Challenge Problems.
  • Desire to improve skills in public presentation of scientific results by giving presentations and participating in the LLNL student poster competition.
  • Eagerness to obtain an understanding of new application areas.
  • Exposure through coursework or relevant experience to some of the following topics: statistical modeling and data analysis, Bayesian and frequentist statistical frameworks, inverse problems, uncertainty quantification, Machine Learning, Computer Vision, multimedia signal and video processing, combinatorics and algorithms, graph modeling and social network analysis, modeling and Simulation

Qualifications We Desire
  • GPA of 3.0 or above.
Additional Information
Why Lawrence Livermore National Laboratory?
  • Included in 2021 Best Places to Work by Glassdoor!
  • Work for a premier innovative national Laboratory
  • Comprehensive Benefits Package
  • Flexible schedules (*depending on project needs)
  • Collaborative, creative, inclusive, and fun team environment

Learn more about our company, selection process, position types and security clearances by visiting our Careersite .

COVID-19 Vaccination Mandate

LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.

Security Clearance

LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory. Most positions will require a DOE L or Q clearance (please reference Security Clearance requirement). If you are selected, wewill initiate a Federal background investigation to determine if youmeet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. An L or Q clearance requires U.S. citizenship. If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted. For additional information please see DOE Order 472.2 .

Equal Employment Opportunity

LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form .

CaliforniaPrivacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here .
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Dice Id : LLNL
Position Id : REF1733W
Originally Posted : 3 months ago
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