Research Scientist - Urban AI

Requisition Id 14933 

­­Overview:  

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

We are seeking a Research Scientist who will focus on the applications of Artificial Intelligence (AI) and Machine Learning (ML) in Urban Systems.  This position resides in the Computational Urban Sciences Group in the Advanced Computational Methods for Engineered System Section, Computational Sciences and Engineering Division, Computing and Computational Sciences Directorate, at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities: 

• Conduct basic and applied research in AI, ML, and Modeling and Simulation, as they apply to urban sciences including the urban health, urban networks (such as, electric grid and transportation networks), and urban disasters with a strong geospatial focus, statistical methods, graph theory, spatial computing, and semantic knowledge discovery with a strong emphasis on domain-driven impact.
• Develop, optimize, and transition algorithm prototypes to robust implementations
• Work with ORNL researchers, as well as internal and external project sponsors, to capture, understand, integrate, and implement their requirements in developed algorithms and software
• Lead technical projects and/or teams and develop and/or collaborate on technical proposals and reports.
• Maintain and enhance a strong scientific publications profile and feasibility in related professional organizations.
• Interpret, report, and present research concepts and results to national audiences at all levels.
• All team members deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• A PhD in Computer Engineering or a related field completed within the last 3 years
• Candidates must have demonstrated expertise in healthcare system optimization and anomaly detection, AI for system modeling and scenarios analysis, anomaly detection in complex systems, and graph-integrated ML for spatial-temporal analysis in smart infrastructure systems.
• Candidates must have demonstrated ability of working with big-data, leading technical teams, developing novel methods, publishing papers in top journals, and having built information systems supporting discovery of scientific insights for urban systems

Preferred Qualifications:

• Expertise in graph analytics and related AI/ML techniques including higher-order network dependencies modeling.
• Expertise in Deep Learning and Machine Learning software libraries with proficiency in using PyTorch and TensorFlow for building and optimizing neural networks, including CNNs, GANs, transformers, and GNNs for urban science applications.
• Expertise in programming languages for software development and data management with proficiency in Python, SQL, Git, Azure Data Studio, pandas, NumPy, and Scikit-learn.
• Experience with High-Performance Computing (HPC) platforms with advanced skills in SLURM-based multi-node, multi-GPU training, data parallelism, and optimization of large-scale machine learning workloads on HPC clusters.
• 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.

Special Requirements:

Letters of Recommendation: 3 number of references are required

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to [email protected] 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

HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge.

About ORNL

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: [email protected].

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 [email protected].

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.