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Postdoctoral Researcher

The University of Kansas
University of Kansas Lawrence Campus

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Position Type
Employment Type
Full Time
Institution Type
Four-Year Institution

Job Details

Position OverviewA postdoctoral research position is available at the University of Kansas in the laboratory of Dr. Sharon Billings. The successful candidate will contribute to a NSF-funded Frontier Research in Earth Science (FRES) award and work with team members at Oregon State University, Colorado School of Mines and Technology, University of California-Riverside, Texas Tech University, Penn State University, Kansas State University, and Boise State University. The goals of the larger project are to quantify when and the degree to which bedrock and roots control subsurface and atmosphere coupling, and the impact of these interactions on water and carbon fluxes. The successful candidate will focus on synthesis of existing data and address one or more questions such as the following, depending on the researcher’s interests:
  1. Exploration of preferential flow controls and relations to soil morphology, aggregate size distribution, and soil moisture with horizon across 7 different systems ranging from grasslands and shortgrass steppe to warm temperate forests and montane forests.
  2. A multidisciplinary approach focused on changes in soil structure that explores soil development, organic matter changes, and interactions of roots and exudates on soils.
  3. Analysis of a continental-scale dataset of soil, vegetation, and climate variables to investigate how land use history can drive soil processes important for biosphere-atmosphere feedbacks, and how those patterns vary with stage of soil development.
  4. Development of spatially explicit products revealing how hillslope position, aspect, and slope influence soil properties in a variety of climates, biomes, and land use histories.
Work on these questions requires some combination of analyses of root distributions, periodic and high frequency soil moisture data, and physical and chemical soil data. Specifically, the individual will:
  • Work with physical or machine learning models to explore drivers of soil structure, preferential flow, depth distributions of soil carbon and nutrient pools, or root water uptake processes
  • Synthesize leveraged datasets into databases for public use, maintain and facilitate sharing of research data with team members and in publicly available respositories; tabulate and display data for presentation in research conferences and for manuscript preparation.
  • Publish results of their work in peer-reviewed literature.
  • Leading or participating in outreach efforts.
  • Assist in the mentoring of undergraduate and graduate students in the laboratory
Job Description80% - Collaboratively conduct research using existing data. Contribute to team meetings by sharing progress. Receiving and implementing changes based on team feedback. Generate manuscripts publishable in top-quality, peer-reviewed journals.

10% - Facilitate data access and version control across faculty, postdoctoral researchers, and graduate/undergraduate students working on the project across the collaborating institutions

5% - Mentor undergraduate researchers for relatively small, related projects

5% - Contribute to research and lab meetings
Position RequirementsThis position works on-site but remote work may be considered per mutual agreement between the department and selected candidate.
Required Qualifications
    Ph.D. in environmental science or related disciplineMotivation to work as a transdisciplinary scientist, receiving and contributing feedback with team members, as evidenced in application materialsAbility to code effectively in R, Python, or MatlabExperience publishing in peer-reviewed literature as evidenced by authoring or co-authoring publications in top-tier journalsAbility to both work in a team and to work independently to solve problems, as evidenced in application materials
NOTE: To be appointed at the Postdoctoral Researcher title, it is necessary to have the PhD conferred at the time of hire. Appointments made without a diploma or certified transcript indicating an earned doctorate are conditional hires and are appointed on an interim basis not to exceed 6-months. Upon verification of degree the appointment will be extended to its full duration.
Preferred Qualifications
    Experience with machine learning techniquesDemonstrated ability in mentoring and/or working with studentsField experience in earth or environmental sciences Experience in a research laboratory setting
Additional Candidate InstructionsA complete online application will include:
  • Cover letter describing how you meet the required and preferred qualifications.
  • Resume
  • List of three (3) professional references
  • Only complete applications will be considered

    Application review begins Monday, June 17th, 2024. For consideration, please apply no later than Sunday, June 16th, 2024.
    Contact Information to ApplicantsDr. Sharon Billings - sharonb@ku.eduAdvertised Salary Range$55,000Work ScheduleMonday - Friday, 40 hours/weekApplication Review BeginsMonday June 17, 2024Anticipated Start DateThursday August 1, 2024Apply to Job


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