Research Scientist, Federated Learning (Hybrid Eligible)

Requisition Id 15623 

Overview:

We are seeking a Research Scientist who will support a growing portfolio of research in large vision-language models, privacy preserving federated learning techniques, and knowledge distillation to target resource-constrained training and inference for resource constrained environments. You are expected to immediately contribute to federated learning and privacy preserving research initiatives, with emphasis on distributed energy resource management. Under the guidance of senior research scientists, the selected applicant will take roles on multidisciplinary teams supporting new research and engineering using ORNL’s Frontier exascale supercomputer for its dense GPU-based HPC resources to train, deploy models and create large-scale production datasets for high-impact sponsor missions. You will be expected to handle sponsor requirements, and develop rapid prototypes to demonstrate new innovations. This position resides in the GeoAI Research Group in the Geographic Data Science Section, Geospatial Science and Human Security (GSHS) Division, National Security Sciences Directorate, at ORNL.

Major Duties/Responsibilities:

• Contribute to the development of workflows that integrate with existing or new large language models and large vision models for resource optimization with energy grid data.
• Provide coding support to implement privacy preserving federated learning techniques.
• Support the design of knowledge distillation methods for resource-constrained training and inference for edge computing scenarios.
• Publish research results in journal articles, conference papers, and technical manuals.
• Lead by example to ensure all work is carried out safely, securely, and in compliance with ORNL policies, standards, and procedures.
• Exemplify a commitment to excellence in research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL.
• Work in a highly collaborative environment with data scientists, machine learning scientists, remote sensing scientists, HPC engineers, Energy grid subject matter experts, and geographers to deliver research and development prototypes. 
• 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:

• PhD in electrical and computer engineering, computer science, applied mathematics or related area and two years of applied experience (professional or academic lab setting).
• Experience in developing federared learning, differential privacy frameworks, pretraining large vision foundation models.
• Strong research profile and be able to conduct independent research.
• Strong written and oral communication skills. 
• The ability to work in a dynamic, team environment. 

Preferred Qualifications:

• Experience working with spatio-temporal datasets, remote sensing imagery, simulations, and time series analysis.
• Experience in the development, evaluation of energy grid data, natural language processing applications.
• Experience finetuning Large Language Models.
• Hands-on experience with training machine learning models on high performance computing infrastructures leveraging GPU accelerators.
• Experience in the development of project research proposals.
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.

Visa sponsorship: Visa sponsorship is available for this position.

Security, Credentialing, and Eligibility Requirements:

• This position requires the ability to obtain and maintain an HSPD-12 PIV badge.
• For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required.
• Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
• To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

• If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment.
• Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.

Hybrid Eligible:

This position is located in Oak Ridge, Tennessee and requires onsite presence. We offer a flexible work environment that supports both the organization and the employee. A hybrid/onsite working arrangement may be available with this position, which provides flexibility to work periodically from your home, while reporting onsite to the Oak Ridge, Tennessee location on a weekly and regular basis.

About ORNL:

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.

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: ORNLRecruiting@ornl.gov.

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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.

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.