Research Associate in Civil and Environmental Engineering

UVA Health

1d • Onsite

About The Position

The University of Virginia, Department of Civil and Environmental Engineering, is seeking applicants for a Post-Doctoral Research Associate to work in the Link Lab with Professor Jon Goodall. The research involves the development and use of smart infrastructure technology (e.g. sensors, predictive models, mobile computing, data science, etc.) to better manage and operate civil infrastructure systems. The research will be conducted at the Link Lab which houses more than 250 faculty and graduate students from multiple departments and conducts pioneering work in Robotics & Autonomous Vehicles, Smart and Connected Health, Hardware for IoT, and Smart Cities. The position will provide a unique opportunity to advance smart infrastructure research and outreach for addressing societal challenges, including flood resilience in urban environments, and assist in the development of data for use in publications and proposals. The work will involve a good mix of theory, algorithm development, programming, and validation.

Requirements

• A Ph.D. in engineering or computer science is required by the start date

Nice To Haves

• Experience in hydrologic and hydraulic modeling in urban environments
• Use of Artificial Intelligence and Machine Learning (AI/ML) in flood monitoring and modeling
• Publishing research in leading scientific journals
• Python programming
• Machine learning
• Hydrodynamic modeling experience

Responsibilities

• Develop and use smart infrastructure technology (e.g., sensors, predictive models, mobile computing, data science) to better manage and operate civil infrastructure systems
• Advance smart infrastructure research and outreach for addressing societal challenges, including flood resilience in urban environments
• Assist in the development of data for use in publications and proposals
• Engage in theory, algorithm development, programming, and validation

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1-10 employees