Requisition Id 16841

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.

The Discrete Algorithms Group at Oak Ridge National Laboratory (ORNL) seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will develop cutting-edge differential privacy techniques for large-scale models across multiple institutions. This position offers a unique opportunity to work with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science.

The successful candidate will design and implement differential privacy solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing efficient techniques that maintain robust privacy guarantees while minimizing performance impact. Additionally, you will optimize the balance between privacy and utility, addressing the challenges of heterogeneous privacy budgets and varying requirements across diverse clients.

Major Duties/Responsibilities:

• Develop and apply differential privacy for large-scale models scientific data to advance research efforts across scientific systems.
• Develop and apply federated learning on distributed and heterogenous datasets.
• Develop more efficient and resilient DP techniques that minimize performance loss while still providing robust privacy guarantees.
• Develop novel privacy-preservation methods that accommodate the diverse privacy requirements of a large number of clients.
• Develop novel mathematically rigorous approaches to optimize the trade-off between privacy and utility especially in the context of large models.
• Advance knowledge of key AI methods such as deep learning, algorithm design, probability theory, privacy definitions, and apply it to develop efficient privacy preserved federated learning model.
• Communicate and coordinate experimental results with other domain experts to facilitate collaboration.
• Present and report research results and publish scientific results in peer-reviewed journals or conferences.

Basic Qualifications:

• A PhD in Computer Science, Applied Mathematics, Computational Science, or related discipline.
• Demonstrated hands-on experience and understanding of developing and applying privacy preservation methods to ML models.
• Demonstrated research experience with AI and ML techniques.

Preferred Qualifications:

• Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions.
• Knowledge of federated learning SOTA algorithms.
• Knowledge of distributed optimization and consensus algorithms.
• Knowledge of large models and hyper-parameter optimization.
• Knowledge of high-performance computing and its applications.
• An excellent record of productive and creative research, as demonstrated by publications in top peer-reviewed journals.
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative and frequently interacting teams of researchers.

Special Requirements:

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 up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

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.

Letters of Recommendation:

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

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

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.

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.