Postdoctoral Associate, Learning from Landscapes

The Husic Research Group within the Department of Civil and Environmental Engineering at Virginia Tech is seeking a postdoctoral associate whose research interest relate to Learning from Landscapes, a modeling framework that leverages interpretable machine learning to understand how landscape connectivity influences water quality. The selected candidate will work alongside and be mentored by Dr. Admin Husic at the Occoquan Watershed Monitoring Laboratory located in Northern Virginia.

The candidate will have the opportunity to contribute on a recent NSF CAREER project that integrates game theory concepts to explain water quality variations across time and space, from local to global scales. The project will leverage large-sample datasets and high-performance computing to advance transferable insights into what controls variable patterns of riverine biogeochemistry. In addition, candidates will have the opportunity to co-develop their own research projects with Prof. Husic.

While the primary focus of this position is to conduct and disseminate research related to human impacts to water quality, the candidate will be provided opportunities to pursue additional career development activities, such as developing new research skills, establishing a professional network, proposal development, mentoring students, preparing research reports, and/or teaching. A mentoring plan will be developed between Prof. Husic and the candidate at the beginning of the position to determine which opportunities best align with the candidate’s career goals. The candidate will be expected to travel to present research at regional and national conferences.

• PhD in civil engineering, hydrology, computer science, or related fields. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Strong communication skills.
• Track record of conducting original research and publishing in peer-reviewed scientific journals.
• Ability to work in a collaborative team setting, as well as an independent researcher.

• Strong computational background and programing experience with applications in water resources.
• Demonstrable a skillset in hydrologic modeling, machine learning, and technical writing.
• Experience with high-frequency aquatic sensing data and explainable artificial intelligence methods.

Restricted

Starting salary will be commensurate with experience and qualifications.

Application review will commence on January 15, 2025, and continue until the position is filled.

The successful candidate will be required to have a criminal conviction check.

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

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