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. 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. What Your Job Will Be Like: Sandia National Laboratories is seeking a postdoctoral researcher to design and conduct analyses of photovoltaic (PV) system data, including image and electrical performance datasets. The work will include applying statistical and machine learning processes to PV image and timeseries data, and creating/validating models to predict and optimize PV module performance. The selected candidate will work on projects funded by the DOE Solar Energy Technologies Office, and the DuraMAT Consortium, to address key challenges to PV module reliability and field efficiency across different operating environments. These projects help ensure the widespread deployment of reliable, high-efficiency photovoltaic technologies and system designs that are essential to the nation’s transition to a cleaner energy future. On a given day, the candidate may be called on to: + Develop python code for PV image or electrical data analysis + Interpret and implement existing python code + Use classical and statistical/machine learning techniques + Publish and present your work to a variety of audiences + Collaborate with others in and outside Sandia Salary for this Postdoctoral Appointee position is set at $90,000 annually. Qualifications We Require: + PhD in engineering, physical sciences, mathematics, computer science or a closely related field + Experience with python programming and code development + Experience with timeseries data and/or image analysis + Proven ability to write and publish peer-reviewed journals Qualifications We Desire: + Academic experience in solar or renewable energy + Experience with PV system data + Experience with python image processing libraries (e.g., open-cv, pillow, scikit-image) + Experience with python machine learning libraries (e.g., scikit-learn, pytorch, tensorflow) + Ability to handle large quantities of data + Experience writing research grants + Ability to work in a multi-disciplinary team environment + Ability to think creatively About Our Team: The Photovoltaics & Materials Tech Department, part of Sandia's Renewable Energy Technologies Group, conducts research and development and applies real world solutions to increase the viability of sustainable and clean energy systems. Research focuses on solar energy photovoltaics (PV), materials chemistry, and device integration for energy generation and energy efficiency. We apply PV and materials research to the following areas: PV cell technologies including Si, CdTe and CIGS thin films, and emerging technologies (i.e., perovskites), advanced PV module designs (i.e., bifacial, split cells conformable), and PV + Storage.

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: http://www.sandia.gov*These benefits vary by job classification.

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. Job ID: 684974