Apply before: 15 September 2022
Posting:
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This project aims to synthesize a global database of harmonized high-frequency soil moisture and associated properties ready for artificial intelligence and machine learning (AI/ML) applications, and develop AI/ML models that embody the control exerted on PF by weather and land characteristics to predict how the occurrence of PF will change with increased rainfall intensity and drought.
The postdoc will work closely with the four PIs (Matthias Sprenger, Lawrence Berkeley National Laboratory (https://eesa.lbl.gov/profiles/matthias-sprenger/), Pamela Sullivan, Oregon State University (https://sites.google.com/oregonstate.edu/sullivanlab/home), John Nimmo, USGS (https://www.usgs.gov/staff-profiles/john-r-nimmo), and Tianfang Xu, Arizona State University (https://search.asu.edu/profile/3515239)) and a diverse group of in total 15 scientists with extensive knowledge on soil physical processes, hydrological modeling, and machine learning applications.
We seek a candidate with the following minimum qualifications:
- PhD in Soil Science, Earth Science, Hydrology, Civil/Environmental Engineering or similar fields
- Ability to write programming code (e.g., Python, R, or Matlab)
- Good communication skills and willingness to work collaboratively in a large team
- Willingness to travel twice to Colorado for team meetings
- Experience in publishing peer-reviewed literature
The following skills would be advantageous for the position:
- Training in soil science
- Training in scientific computing
- Programming skills in Python
- Experience with statistical methods
- Experience with Structured Query Language (SQL); handling large datasets
- Commitment to Diversity, Equity & Inclusion
The postdoc will be employed at Oregon State University, starting salary for postdocs at OSU are $54,840 per year with an annual 3% merit increase in salary depending on performance. More information on postdoc scholar stipends and benefits can be found here.
Applicants should provide a single PDF containing:
- a cover letter that highlights their experience with regard to soil science and programming (coding and statistical experiences)
- a CV including complete publications list
- and contact information for three references
Applications should be uploaded here and Review of application will start on August 15; application will be closed on September 15: https://forms.gle/b8ArkHQkJUkAMe3x9
Please reach out to Matthias Sprenger (msprenger@lbl.gov) if you have any questions.
Dr. Matthias Sprenger
Earth Research Scientist (Hydrology)
Earth & Environmental Sciences Area
Lawrence Berkeley National Laboratory
Watershed Function Project
Personal webpage Researchgate, Twitter