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.
COVID-19 Vaccination Mandate:
Sandia demonstrates its commitment to public safety in the national interest by requiring that all new hires be fully vaccinated or have an approved medical or religious accommodation before commencing employment. The requirement also applies to those who are telecommuting and working virtually.
Any concerns about the ability to meet this requirement should be directed to HR Solutions at (505) 284-4700.
*Salary range is estimated, and actual salary will be determined after consideration of the selected candidate's experience and qualifications, and application of any approved geographic salary differential.
What Your Job Will Be Like:
Join a dynamic team that solves significant issues for our nation’s security! We are seeking a self-directed, results focused Postdoctoral Appointee to support research and development efforts related to development of improved turbulence models for hypersonic applications using machine learning techniques. You will develop and apply data-driven modeling techniques, including generation of training data through high fidelity simulation, in research aimed at improving predictive accuracy of turbulence models for hypersonic flows!
This posting enables flexibility to work in either the Aerosciences Department in Albuquerque, NM, or the Extreme-Scale Data-Science & Analytics Department in Livermore, CA; the location will be determined by the fit of the candidate. The selected applicant can also be a virtual worker located in any U.S. State or District of Columbia. Regular or periodic travel to your assigned work location may be required.
On any given day, you may be called on to:
Design and implement direct numerical simulation or large eddy simulation campaigns of compressible, wall-bounded turbulent flow to generate data for training data-driven models.
Use data-driven modeling techniques, including machine learning methods, to create predictive turbulence models for hypersonic flow.
Implement data-driven models into existing RANS CFD codes and assess and improve their predictive performance and numerical stability.
Participate in the entire life cycle of turbulence model development, from mathematical description to implementation to validation, and publish results in peer-reviewed journals.
Join our team and achieve your dreams!
Qualifications We Require:
PhD, conferred within 5 years prior to employment, in aerospace engineering, mechanical engineering, or a related field (with concentration in fluid dynamics)
Experience simulating compressible turbulent flows with high-fidelity simulation techniques (DNS, LES, or RANS).
Code development experience in a high-level programming language like C++ or FORTRAN for advanced scientific software (CFD, FEA, etc.) on massively parallel computing clusters.
Good communication skills as evidenced by a history of publication of results in peer-reviewed journals and external presentations at appropriate scientific conferences
Only U.S. persons (citizens, lawful permanent residents, asylees or refugees) are eligible for consideration
Qualifications We Desire:
Experience with data-driven turbulence modeling
Experience developing machine-learning models in software packages such as PyTorch or TensorFlow
Significant experience with Python
Experience with scripting languages and grid generation software
Experience with code and solution verification, validation, and uncertainty quantification
Experience working with a diverse team
About Our Team:
The Aerosciences Department offers challenging and important work relating to national security in R&D and technology applications in aerodynamics, aerothermodynamics, compressible fluid mechanics, and flight dynamics. Projects span the Mach number range from subsonic through hypersonic and involve systems ranging from aircraft released ordinance to reentry systems and rocket systems. Technical activities include experimental, analytical, and computational efforts plus support of flight test activities, both pre-flight/post-flight analyses and field test operations. Analogously, 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.
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
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.
Job ID: 684840