1+ months

Machine Learning for Climate Change and Wildfire Risk - Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

Are you passionate about building a secure and sustainable energy future, while protecting critical infrastructure in a changing climate? You will work in a team with leading scientists and engineers in climate science, wildfire research, power grid modeling, advanced machine learning, and high-performance computing to quantify future risks to California's energy infrastructure from wildfires. This project presents a unique opportunity to perform original research while participating in a broad interdisciplinary project that leverages emerging technologies in several fields. This position is in the Atmospheric, Earth, & Energy Division (AEED) within the Physical & Life Sciences (PLS) Directorate.

In this role you will

  • Conduct creative research at the intersection of climate change, wildfire risk, and power grid planning.
  • Develop and apply advanced machine learning methods to atmospheric, surface fuel, and wildfire data.
  • Develop projections of wildfire impact pathways for California's energy infrastructure in a changing climate.
  • Publish research results in peer-reviewed journals and technical reports.
  • Present results at scientific conferences and to various stakeholders.
  • Pursue activities that enhance your technical skills.
  • Interact with a broad spectrum of technical experts internally and externally
  • Perform other duties as assigned

  • PhD in atmosphere, climate, wildfire, or plant canopy research, or a closely related field
  • Experience in one or more of: wildfire models and data, land surface models, plant canopy models, and simulating atmospheric flows in complex terrain.
  • Proficient in at least one scientific programming language for modeling and/or model output data analysis (e.g., Fortran, C++, Python, NCL).
  • Experience performing independent research.
  • Proficient verbal and written communication skills, as evidenced by published results and presentations.
  • Can travel as required to meet with sponsors and achieve important milestones.

Qualifications We Desire

  • Experience in analyzing climate change impacts working with remote sensing data.
  • Experience with uncertainty quantification, ensembles, statistical analysis, and numerical simulation of geophysical processes.
  • Experience collaborating effectively with a team of scientists of diverse backgrounds.

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are those who have been awarded a PhD at time of hire date.

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Why Lawrence Livermore National Laboratory?

  • Included in 2022 Best Places to Work by Glassdoor!
  • Work for a premier innovative national Laboratory
  • Comprehensive Benefits Package
  • Flexible schedules (*depending on project needs)
  • Collaborative, creative, inclusive, and fun team environment

Learn more about our company, selection process, position types and security clearances by visiting our Career site.

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COVID-19 Vaccination Mandate

LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.

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Security Clearance

None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.) For additional information, please see DOE Order 472.2.

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Pre-Employment Drug Test

External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

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Equal Employment Opportunity

LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.

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California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.


Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory's mission.

"},"jobDescription":{"title":"Job Description","text":"

Are you passionate about building a secure and sustainable energy future, while protecting critical infrastructure in a changing climate? You will work in a team with leading scientists and engineers in climate science, wildfire research, power grid modeling, advanced machine learning, and high-performance computing to quantify future risks to California's energy infrastructure from wildfires. This project presents a unique opportunity to perform original research while participating in a broad interdisciplinary project that leverages emerging technologies in several fields. This position is in the Atmospheric, Earth, & Energy Division (AEED) within the Physical & Life Sciences (PLS) Directorate.

In this role you will

  • Conduct creative research at the intersection of climate change, wildfire risk, and power grid planning.
  • Develop and apply advanced machine learning methods to atmospheric, surface fuel, and wildfire data.
  • Develop projections of wildfire impact pathways for California's energy infrastructure in a changing climate.
  • Publish research results in peer-reviewed journals and technical reports.
  • Present results at scientific conferences and to various stakeholders.
  • Pursue activities that enhance your technical skills.
  • Interact with a broad spectrum of technical experts internally and externally
  • Perform other duties as assigned
"},"qualifications":{"title":"Qualifications","text":"
  • PhD in atmosphere, climate, wildfire, or plant canopy research, or a closely related field
  • Experience in one or more of: wildfire models and data, land surface models, plant canopy models, and simulating atmospheric flows in complex terrain.
  • Proficient in at least one scientific programming language for modeling and/or model output data analysis (e.g., Fortran, C++, Python, NCL).
  • Experience performing independent research.
  • Proficient verbal and written communication skills, as evidenced by published results and presentations.
  • Can travel as required to meet with sponsors and achieve important milestones.

Qualifications We Desire

  • Experience in analyzing climate change impacts working with remote sensing data.
  • Experience with uncertainty quantification, ensembles, statistical analysis, and numerical simulation of geophysical processes.
  • Experience collaborating effectively with a team of scientists of diverse backgrounds.

Categories

Posted: 2022-04-26 Expires: 2022-07-28

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Machine Learning for Climate Change and Wildfire Risk - Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

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