IIHR – Hydroscience & Engineering (https://www.iihr.uiowa.edu/) and the Department of Civil and Environmental Engineering at the University of Iowa (https://uiowa.edu/) seek a highly motivated postdoctoral research scholar to join Dr. Gabriele Villarini’s research group (www.gabrielevillarini.com). The initial appointment is full-time for one year, with the possibility of renewal subject to satisfactory performance and continued funding. Research will fall within the broad topics of stochastic hydrology and hydroclimatology. Of particular interest is the examination of spatial and temporal changes in floods, their attribution and projected changes. The research team is open to other related research topics and encourages all qualified applicants to apply.
The successful candidate will have the opportunity to work closely with faculty, staff, and students of IIHR—Hydroscience & Engineering (www.iihr.uiowa.edu), a national and global leader in environmental and fluids-related research, education, and service. The University of Iowa is located in Iowa City, Iowa. Iowa City has been ranked one of the nation’s most livable cities (USA Today, 2006), and one of the best small metropolitan areas for careers (Forbes Magazine, 2013). This small city has a population of about 62,000. It is a community built around higher education, with vibrant cultural opportunities and a long history of international connections, leadership, and accomplishment. Iowa City offers the safe, friendly quality of life for which the Midwest is known.
All qualified applicants are required to apply through https://jobs.uiowa.edu/ by providing a CV, cover letter, and contact information for 3 references. Review of applications will begin as soon as they are received and will continue until the position is filled. For additional information, contact Gabriele Villarini ([email protected]). This advertisement will be posted until position is filled.
Ph.D. in a relevant science or engineering field prior to starting this position is required. Candidates from subsets of fields including hydrology, data science, climate science and applied statistics are particularly encouraged to apply.
Experience in processing and analyzing large data sets and model outputs is required. Expertise in computer programming in R is required. Experience with applied statistics is desirable.