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Requisition Id 9652 

Overview: 

Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.

We are seeking a Postdoctoral Research Associate who will support the Computational Urban Sciences Group in the Computational Sciences and Engineering Division (CSED), Computing and Computational Sciences (CCSD) at Oak Ridge National Laboratory (ORNL). The postdoc will focus on applications of Computational Geometry, Artificial Intelligence and Machine Learning on Urban Systems. The role is expected to use data-driven approaches to develop and foster novel scientific research in the areas of building energy, electric grid and energy systems, transportation systems, natural hazards, and their impact on urban systems, as well as response to other non-natural emergencies. The ideal candidate is expected to bring expertise in the application of AI, data-driven knowledge discovery techniques, and modeling and simulation. Prior experience of applying such knowledge to the understanding of urban systems is preferred.

The Computational Urban Sciences Group is comprised of a multi-disciplinary team of scientists carrying out applied research at the intersection of computing and complex urban systems in the emerging environment of smart cities, energy infrastructures, a modernizing electric grid, smarter and sustainable mobility, responsive buildings, changing impacts of severe weather and climate, and data driven emergency response and resiliency. The advances are enabled by the growing body of technologies that includes big-data, modeling and simulation, machine learning, visualization, graph analytics, geovisualization, high-performance computing, and cloud computing. The candidate must be comfortable working as part of a tightly integrated team and must be capable of supporting multiple projects simultaneously.

Major Duties/Responsibilities: 

• Conduct basic and applied research in Modeling and Simulation, Artificial Intelligence and Machine Learning as they apply to urban sciences including the electric grid, mobility, and buildings with a strong geospatial focus, spatio-temporal and time-series analysis, statistical methods, graph theory, geometry, and semantic knowledge discovery with a strong emphasis on domain-driven impact.
• Develop, optimize, and transition algorithm prototypes to robust implementations
• Work with CSED researchers, as well as internal and external project sponsors, to capture, understand, integrate, and implement their requirements in developed algorithms and software
• Maintain and enhance a strong scientific publication profile
• Interpret, report, and present research concepts and results to national audiences at all levels

Basic Qualifications:

• A PhD in Computer Science, Mathematics, Computer, Computational, or Electrical Engineering or a related field completed within the last 5 years
• Candidates must have demonstrated good academic standing, and the ability to conduct independent and significant research

Preferred Qualifications:

• Experience with big data, streaming data platforms, high-performance computing
• Experience with modeling and simulation
• Past hand-on experience with geospatial techniques
• Strong publication records in the areas of expertise
• Research experience in building energy, transportation data science, natural hazards, emergency response, electric grid, and resiliency strategies
• Excellent written and oral communication skills
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.