Postdoctoral Research Associate - Federated Learning

Oak Ridge National Laboratory • Oak Ridge, TN

69d

About The Position

Do you have a passion for applying artificial intelligence (AI) methods for accelerating scientific discoveries and an ability to think outside of the box in a collaborative and open environment? If so, the Oak Ridge National Laboratory's Learning Systems Group within the Data and Artificial Intelligence Systems section invites you to apply to our new postdoctoral research associate position in AI for science. The Learning Systems Group 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. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also collaborate with ORNL's AI initiative to advance secure, trustworthy, and efficient AI for science. This position offers a unique opportunity to make significant theoretical and applied contributions to differential privacy in federated learning, driving advancements in secure, collaborative AI systems globally. As a postdoctoral researcher, you will help solve some of the most challenging problems faced by the nation. You will perform groundbreaking research on a wide range of significant problems, and you will apply your work to exciting research in multi-disciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and machine learning skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world's fastest computers, and disseminate innovative results through publications and presentations. The Learning Systems Group at the Oak Ridge National Laboratory focuses on artificial intelligence and computational research and applies this knowledge to support the nation's leading initiatives. We hire top researchers who are ready to tackle the hardest problems faced by both the US and the world. Researchers of the Learning Systems group are changing the world with their research, and we are committed to hiring and retaining highly motivated, energetic, and creative individuals that will help us continue our breakthrough scientific endeavors.

Requirements

• A PhD in Computer Science, Applied Mathematics, Computational Science, or related discipline completed within the last 3 years or to be expected in 2025.
• Demonstrated hands-on experience and understanding of developing and applying privacy preservation methods to ML models.
• Demonstrated research experience with federated learning techniques.
• Demonstrated experience working with machine learning and data analytics using tools in programming languages such as Python, PyTorch, Pandas, Scikit Learn, etc., in applied problem-solving contexts.
• Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers).

Nice To Haves

• Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions.
• Knowledge of SOTA federated learning 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.
• Strong problem-solving skills and an interest in interdisciplinary collaboration.
• Commitment to open-source principles and scientific transparency.
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative and frequently interacting teams of researchers.
• Ability to set priorities to accomplish multiple tasks within deadlines and adapt to changing needs.

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.
• Build strong collaborations within ORNL and across the global research community.

Benefits

• ORNL offers competitive pay and benefits programs to attract and retain talented people!
• The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy.
• Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.
• 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
• Employee Discounts

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Professional, Scientific, and Technical Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees