University of Kansas – PhD assistantship in Water Resources Engineering
Dynamic landscapes are a tapestry of hydrologic, environmental, and anthropogenic features that work in tandem to confer ecosystem benefits and provide for societal demands. Increasingly, these landscapes are at risk under the growing pressures of land use alteration and climate change. Understanding how landscapes dynamically connect the transfer of water, sediment, and nutrients is crucial if we are to sustainably manage our shared water resources.
The Department of Civil, Environmental, and Architectural Engineering at the University of Kansas is pleased to announce the availability of a fully-funded PhD position supported by a National Science Foundation CAREER grant. The preferred start date for this assistantship is Summer/Fall 2024. Full consideration will be given to students applying by March 1st.
Research Skills and Areas
- Large-scale water quality modeling, including deep learning and explainable artificial intelligence
- High-frequency aquatic sensing of water, sediment, carbon, and nitrogen
- Forecasting land use and climate change impacts to water quality
Qualifications
- A Bachelor’s (or Master’s) of Science in Civil Engineering or related field
- Completed coursework in the areas of fluid mechanics, hydrology, and statistics
- Knowledge of programming (e.g., Python, R, MATLAB) and statistics
- Excellence in verbal and written communication
Candidates should also be passionate about fostering positive human-environment feedbacks. Funding includes tuition, fees, health insurance, and a full-year stipend. To apply, e-mail a one-page statement of research interest, resume, transcript and GRE scores (if available) to [email protected] (Dr. Admin Husic). For more information visit https://hydraulics.eco/
The University of Kansas is committed to providing an equal opportunity for all qualified individuals, regardless of race, religion, color, ethnicity, sex, disability, national origin, ancestry, age, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression, or genetic information.