Post-Doctoral Researchers:
Climate Legacies and the Carbon Cycle
Expected Start: Position Filled, but we anticipate advertising for a second post-doc in 2025.
Description: An NSF Macrosystems Biology project on “Climate legacies and timescales of influence on carbon cycle processes in drylands” is seeking to hire a post-doctoral scientist to synthesize diverse data sources representing carbon fluxes at different scales across the western USA. Nearly all projects involve working with large datasets and developing and applying sophisticated statistical models to those data. Candidate datasets include tree-ring chronologies from existing networks, flux tower data (e.g., from AmeriFlux and NEON sites), remotely sensed vegetation productivity, and a variety of climate data products. The post-doctoral scientist will have the flexibility to work on projects related to different themes, including: (1) Identifying climate extremes (e.g., droughts or temperature extremes at different time scales) and quantifying the magnitude and duration of associated climate legacies on tree or ecosystem productivity; (2) Evaluating climate memory and the timescales over which climate-related drivers impact C fluxes across varied scales; and/or (3) Exploring how climate legacies and memory vary across different dryland ecosystems in the western USA. The post-doctoral scientist will be part of an enthusiastic and productive research team involving multiple faculty members and graduate students from Northern Arizona University, along with colleagues from the University of California, Los Angeles. There are opportunities to mentor students, contribute to outreach activities (e.g., involving collaborations with stakeholders, co-organizing workshops and conferences, developing educational materials for the public), and/or participating in field campaigns at NEON sites.
Required qualifications: A PhD or equivalent doctorate in a relevant field is required, such as ecology, environmental science, forestry, statistics or data science, such as informatics. Applicants should have experience in statistical modeling (e.g., Bayesian and/or machine learning), coding (e.g., in R) and computing, and working with ecological, environmental, or climate data. Applicants are expected to have a basic understanding of climate science and ecosystem ecology, and a track record of writing and publishing scientific manuscripts.
Desired abilities / qualifications: Competitive candidates should have a background in one or more areas related to dendroecology, Eddy covariance flux tower data, remote sensing of vegetation, or climate data products. They should have experience in one of more technical areas related to machine learning, Bayesian statistical modeling, high-performance computing, and data management and sharing. Experience using R, JAGS, OpenBUGS, STAN, or NIMBLE software is desirable. An ability to communicate and collaborate in research teams is beneficial.
Application procedure: Application materials must include: 1) curriculum vitae, 2) cover letter describing interest in project and background and qualifications relevant to the position, and 3) contact information for at least 3 professional references. All application materials should be submitted electronically in PDF format. To apply, go to the Careers @ NAU link (https://in.nau.edu/human-resources/current-job-openings/), click “Current openings,” then “Career opportunities,” then search “Staff openings” using the vacancy number 606755.
Graduate Students:
Join the PhD program in Ecological and Environmental Informatics (EEI) at Northern Arizona University! Students interested in pursuing a graduate degree under the direction of Dr. Kiona Ogle related to any of the research themes in the Ogle Lab are encouraged to contact Dr. Ogle via email at Kiona [DOT] Ogle [AT] nau [DOT] edu. Dr. Ogle is particularly interested in taking on students with strong quantitative backgrounds, or that have the ability and desire to develop quantitative and computing skills, and that wish to use these skills to address important questions in plant or ecosystem ecology. Students keen on integrating mathematical, simulation, or statistical modeling with empirical or experimental studies to address questions related to one of the Ogle Lab’s research themes should contact Dr. Ogle, and prospective students with compatible interests are encouraged to learn more about the graduate programs at NAU and/or to apply for graduate study through the School of Informatics, Computing, and Cyber Systems (see the EEI PhD program) or the Department of Biological Sciences (see the Biology PhD program).
Undergraduate Students:
The Ogle Lab is frequently looking for NAU undergraduates to help with a variety of ecology or computing related projects. Students often participate in a range of activities that involve anything from data entry to working with large databases to field work to laboratory analyses of field samples. Interested students should contact Dr. Kiona Ogle via email at Kiona [DOT] Ogle [AT] nau [DOT] edu.
