Job description

About Sandia: 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 vacation, 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: sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking a Postdoctoral Appointee. Join a multidisciplinary team to advance trustworthy scientific machine learning (SciML) and data-driven analysis for computational science applications. On any given day, you may be called on to: • Develop and evaluate ML-based surrogates, reduced-order models, and embedded data-driven components within physics-based simulations • Design and execute verification, validation, uncertainty quantification, robustness testing, explainability, and interpretability studies • Apply feature-extraction and pattern-recognition methods: wavelet analysis, tensor/matrix decompositions, energy-based features, anomaly detection, and supervised/unsupervised learning to images, microstructures, sensor data, and high-dimensional simulation outputs • Collaborate with Sandia PIs, national laboratories, and academic partners to integrate, compare, and benchmark data-driven methods against high-fidelity models and experiments Due to the nature of the work, the selected applicant must be able to work onsite in Livermore, CA. Qualifications We Require: • PhD (conferred within 5 years) in applied mathematics, computational science, engineering, statistics, computer science, or a related field • Expertise in machine learning, scientific machine learning, uncertainty quantification, or statistical learning • Experience developing or evaluating ML methods for simulation, image, signal, or high-dimensional data • Ability to obtain and maintain a DOE Q-level security clearance Qualifications We Desire: • Hands-on experience with SciML surrogates, VVUQ, independent model evaluation, robustness, and explainable/interpretable ML • Proficiency in wavelet and spectral analysis, tensor/matrix decomposition, and energy-based feature extraction • Familiarity with supervised/unsupervised learning, classification, clustering, and anomaly detection • Skilled in Python and ML libraries (PyTorch, JAX, TensorFlow, scikit-learn, NumPy, SciPy, pandas, PyWavelets, OpenCV, etc.) About Our Team: The Quantitative Modeling and Analysis Department conducts research, development, and systems engineering in computer science and engineering to address important, complex national security problems. Key research areas include uncertainty quantification, optimization, inference modeling, data analysis, and algorithm development. Much of our application development work focuses on verification, validation and uncertainty quantification of complex problems. We provide trusted design and software development for large, operations software as well as detailed scientific computing software. The work is focused on providing efficient, validated information and technologies for use in predictive modeling and decision making. Posting Duration: This posting will be open for application submissions for a minimum of three (3) calendar days, including the 'posting date'. Sandia reserves the right to extend the posting date at any time. Security Clearance: Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. 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. Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment. EEO: 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. NNSA Requirements for MedPEDs: If you have a Medical Portable Electronic Device (MedPED), such as a pacemaker, defibrillator, drug-releasing pump, hearing aids, or diagnostic equipment and other equipment for measuring, monitoring, and recording body functions such as heartbeat and brain waves, if employed by Sandia National Laboratories you may be required to comply with NNSA security requirements for MedPEDs. If you have a MedPED and you are selected for an on-site interview at Sandia National Laboratories, there may be additional steps necessary to ensure compliance with NNSA security requirements prior to the interview date. Position Information: This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment. Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance. Job ID: 699078 Job Family: 92 Regular/Temporary Position: T Full/Part-Time Status: F

Requirements

Must-haves

We are seeking a Postdoctoral Appointee. Join a multidisciplinary team to advance trustworthy scientific machine learning (SciML) and data-driven analysis for computational science applications.
On any given day, you may be called on to:
Develop and evaluate ML-based surrogates, reduced-order models, and embedded data-driven components within physics-based simulations
Design and execute verification, validation, uncertainty quantification, robustness testing, explainability, and interpretability studies
Collaborate with Sandia PIs, national laboratories, and academic partners to integrate, compare, and benchmark data-driven methods against high-fidelity models and experiments
Due to the nature of the work, the selected applicant must be able to work onsite in Livermore, CA.
PhD (conferred within 5 years) in applied mathematics, computational science, engineering, statistics, computer science, or a related field
Expertise in machine learning, scientific machine learning, uncertainty quantification, or statistical learning
Experience developing or evaluating ML methods for simulation, image, signal, or high-dimensional data
Ability to obtain and maintain a DOE Q-level security clearance
Hands-on experience with SciML surrogates, VVUQ, independent model evaluation, robustness, and explainable/interpretable ML
Proficiency in wavelet and spectral analysis, tensor/matrix decomposition, and energy-based feature extraction
Familiarity with supervised/unsupervised learning, classification, clustering, and anomaly detection
Skilled in Python and ML libraries (PyTorch, JAX, TensorFlow, scikit-learn, NumPy, SciPy, pandas, PyWavelets, OpenCV, etc.)
This posting will be open for application submissions for a minimum of three (3) calendar days, including the 'posting date'. Sandia reserves the right to extend the posting date at any time.
This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment.
Job ID: 699078
Job Family: 92
Regular/Temporary Position: T
Full/Part-Time Status: F

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlpython

Platform: careers-html
Effort: medium

Benefits

Benefits detected in the listing.

401k