Research Scientist, HPC and Al

Date: Apr 9, 2024

Location: Oak Ridge, TN, US, 37831

Company: Oak Ridge National Laboratory

Requisition Id 12680 

 

 

Overview:

 

The Analytics and AI Methods at Scale (AAIMS) group in the National Center for Computational Science (NCCS) is actively seeking driven and hard-working research scientists to join our dynamic team. Positioned at the exciting crossroads of High-Performance Computing (HPC) and Artificial Intelligence (AI) at scale, this role is specifically geared towards using AI for scientific advancements on a large scale. Our ambition is to advance computational science by merging sophisticated AI techniques and methodologies with the capabilities of high-performance computing systems.

Key Research Areas:

  • AI for Science: Engage in the research and development of expansive AI models tailored for scientific applications, emphasizing pre-training, instruction-based fine-tuning, and the incorporation of human-guided reinforcement learning strategies.
  • Responsible AI: Investigate AI methods that preserve privacy, enhance safety, and tackle the challenges and defense mechanisms related to generative AI models.
  • Distributed Machine Learning: Focus on advancing data parallelism, model-parallelism, and collective communication strategies in large-scale setups. Proficiency in frameworks such as DeepSpeed, FSDP, Megatron-LM are highly valued.

 

The NCCS and its Leadership Computing Program (OLCF) provides world class computing facilities to applications across all computational domains and disciplines, and through this position you will be able to impact and further the mission of NCCS and Oak Ridge National Laboratory. We pride ourselves on encouraging an inclusive and dynamic environment that values initiative and creativity.

 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an outstanding 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

 

Major Duties and Responsibilities:

 

  • Lead and/or collaborate with internal and external researchers on a variety of AI/ML-related research projects.
  • Research and develop scalable AI/ML tools and frameworks on leadership computing platforms.
  • Present and report research results, publish scientific results in top-tier AI/NLP/Computing peer-reviewed conferences and journals in a timely fashion.

 

Basic Qualifications:

 

Ph.D. in Computer Science, Computer Engineering, or a field closely related to the job duties of this position.

 

Preferred Qualifications:

  • 3+ years of relevant research experience outside of Ph.D.
  • The prospective candidate should be proficient with deep neural networks, have practical experience working on PyTorch or similar DL frameworks, NLP packages and pipelines, usage and understanding of basic Machine Learning algorithms and tools.
  • Experience leading independent projects at a DOE laboratory or academic settings.
  • Solid record of productive research demonstrated by publications in peer-reviewed AI/NLP/ML conferences or journals, and/or open-source software development.
  • Excellent written and oral communication skills
  • Motivated self-starter with 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 to adapt to ever changing needs.

 

ORNL Ethics and Conduct:

 

As a member of the ORNL scientific community, you will be encouraged to commit to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity

 

Benefits at ORNL:

 

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.

In addition, 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.

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 or call 1.866.963.9545.

 

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.


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