Research Scientist, Urban Sciences

Requisition Id 14056 

Overview: 

The Computational Urban Sciences Group in the Computational Sciences and Engineering Division (CSED) at the Oak Ridge National Laboratory (ORNL) seeks to hire TWO research scientists who will specialize in employing machine learning, statistical learning, modeling and simulation, and high performance computing with applications in urban health, urban disasters, and urban networks. This position involves utilizing computational and data science methodologies to understand how persistent extreme weather and urban dynamics, coupled with exogenous and endogenous uncertainties, impacts the design and operations of complex and adaptive infrastructure systems. Additionally, the role includes addressing various emergencies, such as extreme events and pandemics. The ideal candidate should possess expertise in uncovering knowledge through data-driven approaches, excelling in high-performance computing, optimization, simulation, artificial intelligence, machine learning, and statistical learning. It is crucial that the candidate has previous experience applying these skills to develop models that effectively tackle diverse urban phenomena.

 

The Computational Urban Sciences Group consists of a diverse team of scientists engaged in applied research at the crossroads of computing and intricate urban systems within the emerging context of smart cities. This includes areas like energy infrastructures, modernizing the electric grid, enhancing sustainable mobility, advancing low carbon cities, creating responsive buildings, understanding the evolving impacts of severe weather and climate, and utilizing data-driven approaches for emergency response and resilience. These advancements are made possible by the expanding array of technologies such as big data, modeling and simulation, artificial intelligence, machine learning, visualization, graph analytics, operations research, high-performance computing, and cloud computing. The ideal candidate should feel at ease collaborating within a closely-knit team and possess the ability to contribute to multiple projects concurrently.

 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

 

Major Duties/Responsibilities:

• Conduct fundamental and applied research concerning infrastructure systems (such as electric grids, natural gas, and transportation networks), smart and connected communities, urban well-being, and urban emergencies, with a significant emphasis on AI/ML, Simulation, Mathematical Modeling, and High-Performance Computing.
• Devise innovative approaches to address issues of national significance and strategize and execute the necessary research and development to practically implement these solutions.
• Collaborate with CSED researchers, as well as internal and external project sponsors, to capture, comprehend, incorporate, and actualize their requirements within developed algorithms and software solutions.
• Lead and participate in various R&D initiatives. Work both autonomously and within teams to define prerequisites and proposals, conduct research, and generate functional prototypes for showcasing.
• Uphold and enrich a robust record of scientific publications and engage in external professional associations.

 

Basic Qualifications:

• PhD in computer science; interdisciplinary engineering, civil engineering; transportation sciences; computer engineering; or related disciplines.
• Candidates must have demonstrated ability of working with big-data, stong publication records, and having built information systems supporting discovery of scientific insights for urban systems.

 

Preferred Qualifications:

• Research experience in big data, urban systems resilience, earth system models, health systems,