Data Science Summer Institute Graduate Student Internship

Overview

livermore, CA
USD 9,340.00 per month
Full Time

Skills

Numerical analysisVideoDocumentationResearchMultimediaParallel computingScientific researchA+Design of experimentsModelingComputational ScienceProVisionInnovationMathematicsOperating systemsSupervisionSoftware developmentJavaEvaluationData AnalysisStatisticsTechnical SupportRecruitingSimulationStatistical modelsInterviewingEffective communicationAlgorithmsCMATLABPrivacyHigh performance computingAccountabilityRPythonSocial network analysisComputer visionComputer hardwareDataSecurity managementData ScienceMachine Learning (ML)PlanningCreativityLawEnergyIDEAPASSPresentationsTestingC++EEOEmployee engagementResearch and developmentComputer scienceSecurity clearance

Job Details

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 committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory's mission.

Pay
$9,340.00 Monthly
Please note that the pay is determined by California's Computer Professional Exemption.
Job Description
Position will be closed to applicants on January 26, 2024.

Internship Dates:
May 20, 2024 - August 9, 2024
June 24, 2024 - September 13, 2024

We have multiple openings for our summer internship program in data science. Our openings are for graduate level students or students who have received their Bachelor's or Master's degree 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
  • Provide technical and/or research support to projects in the areas of computational science, numerical methods, mathematics, or other related fields, working with scientists, engineers, and technical staff members.
  • Perform technical assignments of a basic degree of complexity and provide technical support to scientists in scientific research and development projects.
  • Attend data science related short courses, attending meetings and work with other interns on a data science challenge problem.
  • Support documentation, testing, creation, or modification of Laboratory software, hardware, or Computer operating systems.
  • Conduct research in assigned area. Gather and analyze data and information in support of scientific research under limited direction and supervision.
  • Participate in research planning and evaluation discussion.
  • Attend relevant seminars and participate in DSSI related courses, meetings, and events.
  • Present work through presentations and/or poster sessions during your internship.
  • Perform other duties as assigned.
Qualifications
  • Must be a continuing college or university student in good standing at an accredited institution pursuing a graduate degree or has completed their bachelor's or master's 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. Distributed/parallel computing and experience with C/C++ and/or Java a plus.
  • Ability to apply 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
All your information will be kept confidential according to EEO guidelines.

Why Lawrence Livermore National Laboratory?
  • Included in 2022Best 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. Some positions will require a DOE L or Q clearance (please reference Security Clearance requirement above). If you are selected and a clearance is required, 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. 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 .

Why Lawrence Livermore National Laboratory?
  • Holiday Pay
  • Sick leave accrual
  • Individual 401(k) contributions
  • Inclusion, Diversity, Equity and Accountability (IDEA) - visit
  • Our core beliefs - visit
  • Employee engagement - visit

Security Clearance

None required.However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.)

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams:

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. 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.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision .

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.

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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