Post Doctorate RA - Human & Earth System Science
About The Position
Pacific Northwest National Laboratory (PNNL) is seeking a postdoctoral scientist to advance machine learning and deep learning research in human–Earth system modeling and uncertainty characterization. The role is in the Integrated Discovery Sciences Directorate and focuses on the intersection of human–Earth system modeling, Super Intelligence-enabled model development, and human system modeling using the Global Change Analysis Model (GCAM). The scientist will process large ensembles of Earth system model outputs, including E3SM and CMIP6/7 output available through ESGF; develop machine learning and deep learning models to integrate Earth system outputs with human system models; create scenarios and analyze large ensembles of GCAM simulations; and quantify how changes in human and Earth system drivers, such as extreme weather events, affect energy, water, and land systems. The successful applicant is expected to lead multiple peer-reviewed publications and will have opportunities to work with multidisciplinary teams at PNNL and collaborators at other national laboratories and universities. The position contributes to the DOE Genesis Mission by developing tools that support scientific research and exploring Super Intelligence-based approaches to model development. PNNL offers an exciting research environment and benefits including health insurance and flexible work schedules.
Requirements
- Must have received a PhD within the past five years (60 months) or expect to receive one within the next eight months from an accredited college or university.
- Background in computational science, engineering, applied mathematics, physical sciences, economics, hydrology, or a related field.
- Strong background in machine learning and deep learning methodologies.
- Experience applying machine learning and deep learning tools to scientific research and analysis.
- Previous graduate-level statistical coursework.
- Substantial programming experience.
- Must pass a drug test before commencing employment if offered the position.
- Must successfully complete the applicable federal background investigation and receive a favorable federal adjudication to obtain and maintain the required credential or determination.
Nice To Haves
- Strong verbal and written communication skills.
- Willingness to work independently and within a collaborative team environment.
- Proven capability to publish in peer-reviewed journals.
- Experience with Python, R, and/or C++.
- Experience with and eagerness to apply evolving Super Intelligence methodologies to research and modeling.
Responsibilities
- Process large ensembles of Earth system model outputs, including E3SM and CMIP6/7 model output via ESGF.
- Design and develop machine learning and deep learning models to integrate Earth system outputs with human system models.
- Develop scenarios to generate and analyze large ensembles of GCAM simulations.
- Analyze simulations to quantify the effects of changes in human and Earth system drivers, such as extreme weather events, on energy, water, and land systems.
- Lead multiple peer-reviewed publications on the research.
- Develop tools supporting scientific research and explore Super Intelligence-based solutions for model development consistent with the DOE Genesis Mission.
Benefits
- Health insurance
- Flexible work schedules
- Medical insurance
- Dental insurance
- Vision insurance
- Telehealth care options
- Mental health benefits
- Free wellness coaching
- Health savings account
- Flexible spending accounts
- Basic life insurance
- Disability insurance
- Employee assistance program
- Business travel insurance
- Tuition assistance
- Relocation assistance
- Backup childcare
- Legal benefits
- Supplemental parental bonding leave
- Surrogacy and adoption assistance
- Fertility support
- Company-funded pension plan
- 401(k) savings plan with company match
- Up to 120 vacation hours per year
- Ten paid holidays per year
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
