Postdoctoral Appointee: Materials Models and Machine Learning for Energy Sustainability (Hybrid)

Sandia National Laboratories

Livermore, CA

Job posting number: #7244979 (Ref:693414)

Posted: May 15, 2024

Job Description

Bidder Eligibility: 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. Employees must remain in their current position for one year before applying for a new position, with the exception of student interns. Application of this requirement will not supersede collective bargaining agreements. See collective bargaining labor agreements for represented bidder eligibility requirements for represented employees.

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 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:*These benefits vary by job classification. What Your Job Will Be Like: We are seeking a Postdoctoral Appointee/Scientist to apply electronic structure calculations, machine learning, and/or first principles simulations to accelerate materials discovery. Research areas may broadly span inorganic materials modeling (oxides, nitrides, MXenes, transition metal dichalcogenides, or others) for energy and fuels (hydrogen or ammonia production, storage, or utilization), carbon capture, or other applications. A central theme in this effort is the rational design of new materials by changing the chemical composition, the arrangement of the atoms or molecules in crystalline or amorphous configurations, and the size, shape, and orientation of nanoparticles, films, crystals, or other nano- or macroscopic units. Excellent communication skills are required to convey results with multi-disciplinary scientific teams and help prioritize and direct experimental validation efforts. The selected applicant can work a combination of onsite and offsite work. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary. On any given day, you may be called on to: + Demonstrate the creativity and know-how to (1) develop new materials’ featurization strategies and (2) adapt state-of-the-art machine and deep learning techniques to directly predict materials properties that are not achievable within currently established methodologies + Use Density Functional Theory (or other first principles techniques) to acquire any data necessary to train such models when it does not already exist + Integrate the outputs of machine learning models with other physics-based models or classical simulations to predict the thermodynamic, kinetic, or electronic properties of materials + Collaborate with a diverse team of experimentalists and theorists to publish and present high quality research Qualifications We Require: + Ph.D. in materials science, chemistry, physics, materials engineering, or closely related field + A record of scientific research accomplishment, as demonstrated by authorship of publications in peer-reviewed scientific journals that appear on your CV + Research emphasis of applying theory, computational methods (such as density functional theory, ab initio quantum chemistry, and/or atomistic modeling), and/or machine learning to address materials science problems, as documented on your CV Qualifications We Desire: Exceptional applicants will also have previous experience and demonstrated success in some of the following: + High-throughput electronic structure calculations of inorganic materials + Open-source materials science libraries and databases like atomate, ase, pymatgen, Materials Project, OQMD, etc. + Interpretable machine learning techniques to discover new structure-function relationships from experimental or computational data, which will in-turn be used to design novel materials with properties and behavior that are enhanced over existing options + Active learning techniques to iteratively discover better materials + Extensive collaboration skills within a larger team engaged in modeling, material synthesis, and use of advanced characterization tools + Playing a major role in discovery and advancing the fundamental understanding of new materials through state-of-the-art computational and data science tools About Our Team: The Energy Nanomaterials Department is a research organization specializing in the discovery, synthesis and characterization of nanomaterials for energy and national security applications. Projects and capabilities in the department's research portfolio include nanoporous materials for sensing, catalysis, energy harvesting, and gas storage; materials for energy and hydrogen storage; machine learning; and nanoscale materials characterization including extensive electron microscopy and X-ray diffraction. For an example of a recent publication on materials discovery from our group, please see: Posting Duration: 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.

Security Clearance:

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. 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. Job ID: 693414 Job Family: 92 Regular/Temporary Position: T Full/Part-Time Status: F

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

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Job posting number:#7244979 (Ref:693414)
Application Deadline:Open Until Filled
Employer Location:Sandia National Laboratories
Albuquerque,New Mexico
United States
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