DuraMat Research Scientist

LBL • $145K — $159K *
Berkeley, CA 94704In-Person
Energy & Utilities
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Advanced degree in Electrical Engineering, Materials Science, Physics, or related field with 3-5 years of relevant experience.
  • Strong academic record and experience in solar PV analysis and degradation.
  • Skill in developing and maintaining open-source scientific software.
  • Proficient in Python for both frontend and backend applications.
  • Experience preparing funding proposals and managing R&D projects independently.
  • Proven publication record, particularly in lead-author roles on solar PV degradation.
  • Familiarity with statistical data analysis and machine learning for scientific datasets.

Responsibilities

  • Conduct independent research on solar PV module degradation within the DuraMat program.
  • Develop innovative solutions for complex PV degradation challenges.
  • Lead the technical direction of open-source PV analysis tools and platforms.
  • Apply physics-based and machine learning methods for PV degradation analysis.
  • Publish peer-reviewed research and progress to lead-author status.
  • Contribute to funding proposals and present scientific findings to stakeholders.
  • Mentor and supervise junior staff, fostering research collaborations.

Benefits

  • Opportunity for career development with potential for PI status upon training completion.
  • Full-time, multi-year appointment with renewable options based on performance.
  • Engagement in a collaborative research environment with multiple institutions.
  • Access to advanced research tools and resources in a leading scientific organization.
Full Job Description
The Career-Track Research Scientist in the Energy Technologies and Systems Division will conduct research on solar photovoltaic (PV) module degradation within the DOE CMEI DuraMat Program and lead the development of the group's open-source PV degradation analysis tools. This role includes developing physics-based and statistical methods for PV degradation analysis, building agentic AI systems for autonomous PV and materials data analysis, conducting independent research, contributing to funding proposals, and providing scientific leadership to junior staff. You will be eligible for PI status upon completing required training.

You will:
  • Develop innovative solutions to complex PV degradation challenges, leading independent projects and contributing to multi-institutional research efforts.
  • Lead the development and technical direction of the group's open-source PV analysis tools (PVPRO, Vocmax) and the pvtools.lbl.gov platform, including new physics-based and data-driven degradation models.
  • Develop and apply physics-based, statistical, and machine learning methods to analyze PV degradation from operational and I-V data.
  • Build agentic AI systems and Python-based tools for autonomous PV and materials data analysis.
  • Conduct research within the DuraMat program, progressing to an independent research program by the Mid-Term Evaluation.
  • Publish peer-reviewed research, progressing to lead-author publications by the Mid-Term Evaluation.
  • Contribute to funding proposals and submit proposals by the Mid-Term Evaluation.
  • Present research at conferences and seminars, and report progress to DOE program managers.
  • Supervise and mentor junior staff and students.
  • Build and maintain collaborations across the research community.


Additional Responsibilities as needed:
  • Act as liaison between PIs / Scientists, other LBNL employees, and external contacts.


We are looking for:
  • Advanced degree in Electrical Engineering, Materials Science, Physics, or a related field, and 3-5 years of relevant professional experience.
  • Excellent academic record and evaluations
  • Demonstrated experience applying advanced principles, theories, and concepts to R&D problems in solar PV analysis and degradation
  • Demonstrated experience developing and maintaining open-source scientific software
  • Significant experience programming in Python on both frontend (e.g., Plotly Dash) and backend (e.g., numpy, scipy)
  • Demonstrated experience preparing funding proposals, and independently planning and completing projects
  • Proven record of publications and achievements, including lead-author publications on solar PV module degradation analysis (e.g., circuit-model parameter extraction, I-V curve correction, degraded-system power modeling)
  • Ability to apply advanced principles, theories, and concepts to R&D problems in PV degradation analysis, and to conduct creative research progressing toward independent direction
  • Proficiency in Python (frontend and backend) and scientific computing
  • General knowledge of solar photovoltaics, module degradation mechanisms, and PV performance analysis (pvlib, rdtools)
  • Prior experience with statistical data analysis and/or machine learning applied to scientific data
  • Programmatic LLM usage within agentic frameworks
  • Ability to collaborate effectively with a multidisciplinary team of scientists, industry partners, and international collaborators
  • Excellent verbal, written, and presentation skills
  • Ability to work effectively both independently and in a team environment
  • Excellent time management and ability to prioritize competing deadlines


Desired skills/knowledge:
  • Ph.D. in Electrical Engineering, Materials Science, Physics, or a related field, and 3-5 years of relevant professional experience
  • Experience working in collaborative multi-lab teams
  • Frontend deployment and maintenance experience (e.g., Heroku, Google Analytics)


Requested Application Materials:
  • Curriculum Vitae.
  • Publication list
  • Statement of research experience and interests.
  • Names and contact information for at least three individuals who can write letters of reference


Internally posted until July 29, 2026.

The position will be exclusively available to current Berkeley Lab employees and those in layoff status with preferential rehire rights from Berkeley Lab until the date listed above. Current Berkeley Lab employees interested in a lateral transfer or promotional opportunity should apply online to be considered.

Additional information:
  • Application date: Priority consideration will be given to candidates who apply by July 29, 2026. Applications will be accepted until the job posting is removed.
  • Appointment type: This is a full-time, 1 year, career-track term appointment that may be renewed to a maximum of five years and that may be converted to career based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
  • Salary range: The expected salary for this position is $145,524 - $159,168, which fits into the full salary of $94,740 - $227,376 depending upon the candidate's skills, knowledge, and abilities. This includes education, certifications, and years of experience.
  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  • Work modality: This position will be performed on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
  • Relocation: This position is not eligible for relocation assistance.
  • Work authorization: Candidates must be eligible to work in the U.S. at the time of hire. Visa sponsorship is not available for this position.


Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

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