Postdoctoral Research Associate

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 80,000 - 110,000; Full time

Job summary

An established industry player is seeking a postdoctoral researcher to join a dynamic team focused on advancing decentralized intelligence techniques for scientific workflows. This role involves collaborating with leading scientists and leveraging the computational power of the Frontier supercomputer to develop innovative solutions tailored for large-scale scientific applications. The successful candidate will have the opportunity to make significant contributions to both theoretical and applied aspects of distributed intelligence, driving advancements in resilient, adaptive AI systems. If you're passionate about cutting-edge research and want to make a difference in scientific workflows, this position offers an exciting opportunity.

Benefits

Medical and Retirement Plans

Flexible Work Hours

On-site Fitness Facilities

Cafeteria Facilities

Generous Vacation and Holidays

Parental Leave

Relocation Assistance

Employee Discounts

Wellness Programs

Educational Assistance

Qualifications

• PhD completed within the last five years in a related field.
• Hands-on experience with distributed intelligence methods.

Responsibilities

• Develop decentralized methods for scientific workflows.
• Collaborate with scientists to optimize performance and resilience.

Skills

Distributed Intelligence

Large Language Models (LLMs)

Workflow Management

Resource Optimization

Distributed Systems

AI Techniques

Education

PhD in Computer Science

PhD in Applied Mathematics

PhD in Computational Science

Job description

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The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher with expertise in distributed intelligence, reasoning models, LLMs, workflow management, and distributed systems to contribute to the development of advanced decentralized intelligence techniques for scientific workflows deployed across heterogeneous computing resources. As a postdoctoral fellow at ORNL, you will join a dynamic team of researchers specializing in workflow management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale system.

In this role, you will collaborate with leading scientists to design and implement distributed intelligence solutions tailored for large-scale scientific workflows in DOE environments. Your work will be pivotal in advancing the state of the art in resilient infrastructure by developing more efficient and adaptive techniques that maintain robust performance guarantees while optimizing resource utilization across the computing continuum. Additionally, you will investigate innovative approaches to optimize the balance between performance and resilience, considering the complexities of heterogeneous resources and varying workflow requirements across diverse scientific applications.

The successful candidate will have the opportunity to use the computational power of the Frontier supercomputer to scale and validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project ( https://swarm-workflows.org/ ) members to advance robust, performant, and fault-tolerant execution of DOE scientific workflows. This position offers a unique opportunity to make significant contributions to both theoretical and applied aspects of distributed intelligence, driving advancements in resilient, adaptive AI systems on a global scale.

Responsibilities include, but not limited to:

• Develop novel decentralized methods that accommodate the diverse requirements of scientific workflows across the computing continuum.
• Develop and apply LLM-enabled swarm intelligence techniques for large-scale scientific workflows to advance research efforts across DOE scientific applications.
• Develop and apply distributed intelligence methods on heterogeneous computing resources from edge devices to leadership-class systems.
• Develop novel mathematically rigorous approaches to optimize the trade-off between performance and resilience especially in the context of large-scale distributed systems.
• 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 completed within the last five years.
• Demonstrated hands-on experience and understanding of developing and applying distributed intelligence methods to workflows and resource management problems.
• Demonstrated research experience with AI and distributed systems techniques.

Preferred Qualifications:

• Knowledge of distributed intelligence algorithms and emergent behavior systems.
• Knowledge of distributed scientific workflow management and resource orchestration.
• Knowledge of fault-tolerance and resilience techniques in distributed systems.
• Knowledge of high-performance computing and its applications across the computing continuum.
• 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 PhD 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.

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

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: [e-mail]

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 [e-mail].

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.