PhD student opportunities on ecosystem modeling and remote sensing at UW-Madison

The Chen Group at the Department of Forest and Wildlife Ecology of the University of Wisconsin-Madison has positions opening 1-2 fully funded PhD students on Ecosystem modeling and remote sensing. The enrollment time is flexible. The students will also have opportunities to work with scientists at other prestigious institutions and national laboratories.

Our group is particularly interested in questions regarding to the interactions between climate change, terrestrial ecosystems and human society. We develop and use Earth system models (both process-based and empirical), various remote sensing and field data, integrated assessment models and model-data fusion as the major research tools to answer our research questions. For more information about Dr. Chen, please visit https://forestandwildlifeecology.wisc.edu/people/faculty-and-staff/min-chen/.

We are looking for talented and motivated students who are expected to work on one or more of the following general topics:

1) Modeling the land-atmosphere exchanges of carbon, water and energy across different spatial and temporal scales.

2) Vegetation radiative transfer modeling and its applications in understanding ecosystem processes in combination with Earth system models and remote sensing.

3) Using remote sensing data for understanding how ecosystem carbon/water/energy cycle respond to environmental changes.

4) Linking natural Earth system model with integrated assessment model (e.g., GCAM) to understand human-Earth system interactions that infers policy making.

All applicants should meet the minimum requirements by the graduate admission (https://grad.wisc.edu/apply/). International students should also meet the minimum requirement of TOEFL or IELTS. Strong programming skills is desired. Proficiency in spoken/written English is mandatory.

Prospective students are encouraged to contact Dr. Min Chen (mchen392@wisc.edu) to discuss potential research projects and opportunities before their applications. Please include your transcripts, CV, names and contact information of up-to-three references and a personal statement that describes your research interest, experiences and skills relevant to our lab’s research directions. We greatly appreciate all the applications, but we will only give feedbacks to the candidates that we plan to interview.