Research Prime

Computational Scientist, Large Scale Simulation

Organisation Name: ORNL
Organisation Type:
City:
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Country: United States

Job Description:

Requisition Id11477

Overview:

The Scalable Engineering Applications (SEA) Group in the Computational Sciences and Engineering Division is seeking a computational scientist with expertise in high performance computing and numerical methods to develop high-fidelity computational tools that are used for large-scale physics-based simulations of a variety of science applications in the national interest. Our group mission is to use innovative computational science to deliver scalable modeling and simulation tools for engineering applications. We develop and apply new scalable algorithms for advanced computing architectures and use the latest advancements in numerical methods and performance portability for high performance computing. This includes designing and crafting novel software packages at the confluence of modern engineering and computational science which are then deployed as production capabilities to a network of subject matter expert collaborators throughout ORNL and DOE.

In this role you will work with groups across the lab to develop high-quality large-scale multiphysics simulation codes for science applications that are required to run at scales ranging from small simulations that can be done on a laptop computer to very large simulations that require leadership-level hybrid architecture computational resources such as the Frontier supercomputer. Our team is comprised of computational scientists across a diverse spectrum of technical backgrounds ranging from applied mathematics to nuclear engineering. Using the latest advancements in computational methods we build high-quality high-performance code that meets our customers needs and we ensure code quality by integrating modern software development techniques into all products we develop from repository management to unit and regression testing to continuous integration and deployment.

As a U.S. Department of Energy (DOE) Office of Science national laboratory ORNL has an extraordinary 80-year history of solving the nations biggest problems. We have a dedicated and creative staff of over 6000 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 ORNLs broader mission to accelerate scientific discoveries and their translation into energy environment and security solutions for the nation.

Major Duties/Responsibilities:

  • Participate in new and ongoing research in computational science applied to engineering systems including but not limited to: Computational Fluid Dynamics (CFD) Magnetohydrodynamics (MHD) Electromagnetics and Plasma Physics

  • Build new advancements in the scientific application of Finite Element Methods (FEM) linear and nonlinear solvers Artificial Intelligence and Machine Learning (AI/ML) Automatic Differentiation (AD) unstructured mesh generation and software development methods for performance portability on heterogenous systems.

  • Formulate novel solutions to problems of national interest and plan and execute the research and development necessary for the practical implementation of those solutions.

  • Lead and take part in multiple R&D projects.

  • Interpret report and present research concepts and results to national audiences at all levels.

  • Work independently and in teams to develop requirements and proposals conduct research and produce working prototypes for demonstration.

  • Write peer-reviewed papers technical reports and proposals for internal and external release and must represent the organization by giving technical presentations in large public forums.

  • Lead and maintain a strong publication record.

Basic Qualifications:

  • PhD in computer science; computational science; mechanical engineering; aerospace engineering; nuclear engineering; chemical engineering; engineering physics; applied math; physics; or related fields.

  • Prior experience working with high performance computing systems experience in scientific software development and a shown ability in developing and assessing computational algorithms and numerical methods for large-scale simulations.

Preferred Qualifications:

  • Experience with parallel computing techniques including HPC in a Linux environment

  • Familiarity with C++ and GPU programming

  • Experience with distributed computing using the Message Passing Interface (MPI)

  • Experience with modern software development practices to ensure code quality

  • Experience with numerical methods for sparse linear solvers nonlinear solvers and/or time integration

  • Experience with finite element methods and/or mesh generation algorithms for unstructured meshes

  • Experience with applications in Computational Fluid Dynamics (CFD) Magnetohydrodynamics (MHD) Electromagnetics and/or Plasma Physics

  • Experience in applying Artificial Intelligence and Machine Learning (AI/ML) and/or Automatic Differentiation (AD) to scientific problems

  • Excellent written and oral communication skills

  • Ability to work with a measure of autonomy and a willingness to participate creatively in a collaborative team environment

Special Requirements:

  • This position requires access to technology that is subject to export control requirements and to sensitive projects. Successful candidates must be qualified for such access without an export control license.

  • This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such this position is a Workplace Substance Abuse program (WSAP) testing designed position which requires passing a pre-placement drug test and participation in an ongoing random drug testing program in which employees are subject to being randomly selected for testing. The occupant of this position will also be subject to an ongoing requirement to report to ORNL any drug-related arrest or conviction or receipt of a positive drug test result.

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.

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.


Nearest Major Market: Knoxville


Posting Date: Aug 29, 2023
Closing Date:
Organisation Website/Careers Page: https://jobs.ornl.gov/job/Oak-Ridge-Computational-Scientist%2C-Large-Scale-Simulation-TN-37830/1068064300/


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