Research Scientist - AI/Data Sciences and Applied Mathematics

Requisition Id15464

Overview:

The Mathematics in Computation (MiC) Section at The Oak Ridge National Laboratory (ORNL) invites outstanding candidates to apply for a staff position in the Data Analysis and Machine Learning Group. This group focuses on scientific computing with a strong emphasis on scientific machine learning and data analysis.

We are specifically interested in applicants with expertise in one or more of the following research areas:

• The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets;
• Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing;
• The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence in predictions and compressed quantities of interest on defined domains;
• Fast and scalable algorithms to fit the proposed models to data, with a theory that explains the convergence and success of these techniques
• Detailed re-analysis of the performance of the trained models to determine underlying processes that govern the given data.

This job offers an excellent opportunity to conduct exceptional and innovative research in mathematics, statistics and scientific computing, for applications with scientific and national priority. ORNL's mathematics research efforts provide the fundamental mathematical methods and algorithms needed to model complex physical, chemical, and biological systems. ORNL's computational science research efforts enable scientists to efficiently implement these models at the extreme scale of computing and to store, manage, analyze, and visualize the massive amounts of data that result. ORNL's artificial intelligence research provides the techniques to link the data producers, e.g., supercomputers and large experimental facilities, with the data consumers, i.e., scientists who need the data.

Major Duties and Responsibilities:

The position requires collaboration within a multi-disciplinary research environment consisting of mathematicians, computational and computer scientists, and domain scientists (both theoretical and experimental) conducting basic and applied research in support of the Laboratory's mission. Specific responsibilities include:

• Participating in the development of innovative theoretical analysis and computational methodologies for data analysis and/or machine learning technologies, customized to large-scale scientific applications. These include areas such as additive manufacturing, quantum material design, scientific data reconstruction, for material discovery, inverse methods, complex optimization, population and evolutionary dynamics, cyber security and power grid analysis, and uncertainty quantification for engineered systems.
• Collaboration with experts from various scientific disciplines and applications, and following team planning, goals and quality processes.
• Authoring peer reviewed papers, technical papers, reports and proposals.
• Maintaining memberships in professional, academic, and research organizations.

Questions related to this position: Contact Dr. Juan M Restrepo (restrepojm@ornl.gov). Please reference DAML Staff.

Application Requirements:

• A complete curriculum vitae;
• Aresearch statement, including the technical background and significance of the research;
• A list of the names and email addresses of three referees that are qualified to describe the applicant's distinct contributions to their field of research, the impact of their research and their potential for success. Please have this list sent to Mr. Tyler Davidson davidsontg@ornl.gov with "DAML Staff" as the subject line. We will only contact these referees in the event that the candidate is short-listed for the position;
• Optionally, one or two peer-refereed articles, representative of the candidates' research.

Basic Qualifications:

• Ph.D. in Mathematics, Statistics, Computer, Computational Sciences or a field relevant to the job duties of this position.
• Demonstrated record of peer-reviewed research.
• The ability to obtain and maintain a national security clearance.

Preferred Qualifications:

One or more of the following:

• Expertise in numerical analysis.
• Expertise in theoretical machine learning.
• Expertise in the development of artificial intelligence techniques.

• Experience in the design and implementation of scalable numerical algorithms on High performance computing architectures.
• Experience working with modern machine learning software tools and frameworks.
• Experience or the ability to work in large research teams.
• Demonstrated superior written and oral communication skills.
• Effective interpersonal skills.

Security, Credentialing, and Eligibility Requirements:
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.

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.

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.