Sandia National Laboratories Intern - Computational Methods, R&D Grad Year Round in Livermore, California
We are seeking an Intern - Computational Methods, R&D Grad Year Round
As an R&D graduate intern at Sandia, you will work on computational methods development and implementation at the intersection of Bayesian inference, Machine Learning, and Experimental Design. You will work with a team of researchers on a project that seeks to develop the theory and algorithms necessary to enable closed-loop machine learning for complex tasks like active learning, optimization, and control. Potential research activities include investigating novel formulations of variational inference, robust Bayesian analysis, and experimental design for use within machine learning; developing the associated computational methods; and implementing testing environments to study these approaches. This position will involve significant collaboration with researchers within Sandia and at other academic institutions.
On any given day, you may be called upon to:
Work as part of a technical team conducting innovative research in foundational or applied data science
Apply data science capabilities to scientific and engineering applications relevant to Sandia’s diverse mission space
Publish outstanding new developments in peer-reviewed scientific journals
Contribute to development of open-source software
Interact and cooperate with a diverse set of colleagues
This posting will be open for application submissions for a minimum of seven (7) calendar days, including the ‘posting date’. Sandia reserves the right to extend the posting date at any time.
You bring the confidence and skills to be eligible for the job by meeting these minimum requirements:
Earned bachelor's degree
Currently attending and enrolled full time in an accredited science, engineering, or math graduate program
Minimum cumulative GPA of 3.0/4.0
Ability to work up to 30 hours per week during the academic year, and up to 40 hours per week during the summer
Pursuing a Ph.D. in computer science, applied mathematics, or a related engineering or science subject area
Technical expertise in Bayesian Neural Networks, Probabilistic Programming, and/or Variational Inference
Experience with ML platforms like Jax or NumPyro
Publication record indicative of relevant research expertise
Excellent written and verbal communication and interpersonal skills
Experience in high performance, distributed, or parallel computing
Ability to work in collaborative, interdisciplinary research environments on problems comprising diverse application domains
A background in solving practical problems in science and engineering that involve encounters with real-world data
Proven research community leadership through activities such as participation in student or professional organizations, outreach activities, etc.
Related professional experience such as internships in industry or at other national labs, participation in visiting research programs, etc.
Proven software development experience in C++, C, Matlab, R, Python, Julia, or related languages
Sandia's Extreme-scale Data Science & Analytics department provides strong expertise in data science and analytics, supporting Sandia's physical sciences and engineering mission partners by enabling the extraction of critical insights from extreme-scale observations, simulations and experiments. Capabilities in the department combine recent advances in applied mathematics and computer science, with expertise in uncertainty quantification, reduced order modeling, linear/multilinear methods, nonlinear optimization, and feature identification techniques. These capabilities complement and leverage existing research in other Sandia departments.
Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:• Challenging work with amazing impact that contributes to security, peace, and freedom worldwide• Extraordinary co-workers• Some of the best tools, equipment, and research facilities in the world• Career advancement and enrichment opportunities• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)• Generous vacations, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*
World-changing technologies. Life-changing careers. Learn more about Sandia at: http://www.sandia.gov*These benefits vary by job classification.
This position does not currently require a Department of Energy (DOE) security clearance.
Sandia will conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Furthermore, employees in New Mexico need to pass a U.S. Air Force background screen for access to Kirtland Air Force Base. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause access to be denied or terminated, resulting in the inability to perform the duties assigned and subsequent termination of employment.
If hired without a clearance and it subsequently becomes necessary to obtain and maintain one for the position, or you bid on positions that require a clearance, a pre-processing background review may be conducted prior to a required federal background investigation. Applicants for a DOE security clearance need to be U.S. citizens. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.
Members of the workforce (MOWs) hired at Sandia who require uncleared access for greater than 179 days during their employment, are required to go through the Uncleared Personal Identity Verification (UPIV) process. Access includes physical and/or cyber (logical) access, as well as remote access to any NNSA information technology (IT) systems. UPIV requirements are not applicable to individuals who require a DOE personnel security clearance for the performance of their SNL employment or to foreign nationals. The UPIV process will include the completion of a USAccess Enrollment, SF-85 (Questionnaire for Non-Sensitive Positions) and OF-306 (Declaration of for Federal Employment). An unfavorable UPIV determination will result in immediate retrieval of the SNL issued badge, removal of cyber (logical) access and/or removal from SNL subcontract. All MOWs may appeal the unfavorable UPIV determination to DOE/NNSA immediately. If the appeal is unsuccessful, the MOW may try to go through the UPIV process one year after the decision date.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.