Graduate positions with Nicholas McKay

Three funded PhD positions are open in the Paleoclimate Dynamics Laboratory, each on a different project. All can begin in Spring or Fall 2027.

Paleoclimate data assimilation for North American ecosystem research

Funding: NSF-funded project · Duration: 4 years

How much climate change can an ecosystem absorb before its boundaries move? North America warmed by roughly 6°C between the Last Glacial Maximum and today, a natural experiment comparable in magnitude to the warming projected for this century. This NSF-funded collaboration, led by Jack Williams at the University of Wisconsin-Madison, uses that 21,000-year record to quantify how the continent’s major ecosystem boundaries, from Arctic treeline to the prairie-forest edge, responded as climate changed around them. NAU leads the climate side: building the reconstructions the ecosystem analysis depends on.

Working with Dr. McKay and Dr. Michael Erb, you will develop new paleoclimate reconstructions for North America using paleoclimate data assimilation, which fuses proxy records (lake sediments, speleothems, ice cores) with physics-based climate models and statistical downscaling. You will build on infrastructure our group maintains, including the LiPDverse proxy database and the PReSto reconstruction platform, and your reconstructions will feed the ecosystem-sensitivity analyses at partner institutions.

Ideal candidate: strong background in Earth sciences, climate science, or a related field; interest in quantitative methods; programming experience (R, Python); enthusiasm for interdisciplinary collaboration.

Wildfire smoke exposure and aerosol science

Funding: privately funded NAU-Cornell collaboration, with teaching assistantship support · Duration: 5 years

Firefighters work in smoke for long hours, yet sustained crew-level exposure measurements barely exist, and available smoke forecasts cannot resolve the terrain, convection, and drainage flows that control where smoke goes. This NAU-Cornell collaboration tackles both problems with Flagstaff-area fire managers.

You will help lead the Arizona side of the project, shaping your dissertation around firefighter exposure measurement with compact sensor kits and personal aerosol samplers, high-resolution smoke forecasting pairing WRF simulations with machine-learning downscaling, or aerosol composition analysis of smoke samples for heavy metals and biological contaminants. The project includes a semester embedded with collaborators at Cornell.

Ideal candidate: background in atmospheric science, environmental science, engineering, or a related field; enthusiasm for fieldwork and community partners; interest in sensors, data analysis, or machine learning.

AI lake model emulators and the Holocene climate conundrum

Funding: NSF-funded collaboration (NAU, University at Buffalo, University of Montana) · Duration: 4 years

Climate models and proxy reconstructions disagree about global temperature over the past 12,000 years, a mismatch known as the Holocene Conundrum. A leading hypothesis is that proxies, many from lake sediments, record particular seasons rather than the whole year. This project tests that hypothesis at global scale by making lake process models fast enough to run everywhere: physics-informed machine-learning emulators of a widely used lake model, an AI downscaling pipeline, and a Bayesian framework that confronts the results with a global compilation of Holocene lake temperature records.

You will join a team spanning three institutions, working with deep-learning architectures for emulation and downscaling, paleoclimate model output and proxy data, and the Bayesian seasonality analysis. Your dissertation can emphasize the machine learning, the paleoclimate dynamics, or both.

Ideal candidate: background in Earth or climate science, physics, computer science, data science, or a related quantitative field; programming experience (Python preferred); interest in machine learning and open-source scientific software.

How to apply

Contact Dr. McKay directly with your CV, research interests, and a brief statement of why the project appeals to you. Early inquiries are encouraged. He is also always interested in hearing from motivated students and collaborators about other projects.