A postdoctoral fellowship is available for a highly qualified individual to join the Cooperative Institute for Great Lakes Research (CIGLR: https://ciglr.seas.umich.edu/). The successful candidate will work with the climate modeling team at CIGLR to improve our understanding of climate change and variability in the Great Lakes region. The candidate will work on an NSF-funded hydrodynamic modeling project, utilizing the Finite Volume Community Ocean Model (FVCOM) to investigate changes in thermal structure, ice dynamics, and overturning behavior in the North American Great Lakes. This work will focus on two overarching research questions:
- How have extreme events and climate variability in the Great Lakes changed over time, and how do we expect them to change in the future?
- What role do teleconnection patterns (e.g., El Nino/Southern Oscillation, North Atlantic Oscillation) and low-frequency climate oscillations (e.g., Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation) play in controlling Great Lakes climate variability and extreme events?
While the initial geographical focus is on the Great Lakes, the postdoc fellow is welcome to explore potential expansion of their research to other large temperate lakes. The postdoc will be expected to maintain a strong record of scholarly publication, and present at scientific conferences and public meetings.
The successful applicant's appointment will be with CIGLR, which is part of the University of Michigan's School for Environment and Sustainability located in Ann Arbor, Michigan. CIGLR's mission is to lead research, develop applications and products, and engage with stakeholders to achieve environmental, economic, and social sustainability in the Great Lakes. CIGLR is a collaboration between the University of Michigan and NOAA that brings together experts from academia and government research labs to work on pressing problems facing the Great Lakes region. The fellow will spend most of their time at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor and work in close collaboration with colleagues at the University of Michigan.
- A Ph.D. in physical oceanography, atmospheric sciences, or a similar field, with a strong background in ocean or/and ice modeling.
- Familiarity with data analysis and visualization in a scripting environment using R, Python, or similar software.
- Experience with running simulations on a supercomputer or cluster computing environment.
- Strong communication skills. and demonstrated ability to work both as a team and independently.
- Demonstrated ability to lead the development of manuscripts for refereed journal publication.