Research Associate in Physics (Oak Ridge National Laboratory)

Location: Oak Ridge, TN, US 37830 Company: Oak Ridge National Laboratory Requisition ID: 15527 Overview 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. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods to advance multi-scale coupled physics simulations in support of the missions and programs of the US Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s leadership class Computing Facilities (LCFs). The successful candidate will demonstrate strong expertise and skills in computational materials, data analytics, development of surrogate and generative DL models, high-performance computing (HPC), and computational sciences. Major Duties and Responsibilities Participate in: Design and implementation of scalable DL algorithms for atomistic materials modeling applications Design and architecture of integrated, hybrid, atomistic simulation software packages (e.g., LAMMPS) and DL models Documentation, verification and validation, and software quality activities Author peer-reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research in support of the Laboratory’s missions Engage with the broader DL community to develop and apply scalable physics-informed DL techniques to application areas of interest to the CCP group Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service Promote equal opportunity by fostering a respectful workplace in how we treat one another, work together, and measure success Basic Qualifications A PhD in materials science, applied mathematics, computer science, or an AI-related field completed within the last 5 years Demonstrated expertise in atomistic materials modeling for organic, inorganic, and/or hybrid compounds Demonstrated experience with open-source classical molecular dynamics software LAMMPS Demonstrated expertise in writing advanced software in Python Demonstrated experience with the LINUX operating system, LaTeX, Git, Python Demonstrated expertise in the design and implementation of deep learning algorithms in PyTorch Expertise in object-oriented programming and scripting languages Parallel algorithm and software development using the message-passing interface (MPI), particularly as applied to AI/ML algorithms Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills Preferred Qualifications Experience working in a multi-disciplinary research environment that follows modern software quality standards (version control, unit testing, continuous integration, etc.) Experience in the development of large-scale physics simulation codes, including computational scaling and efficiency, for hybrid exascale supercomputing systems Programming model experience for multicore and heterogeneous architectures such as graphical processing units (GPUs) Motivated self-starter with the ability to work independently and 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 adapt to ever-changing needs Appointment Terms Applicants cannot have received their Ph.D. 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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding. Application Instructions Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application. Please submit three letters of reference when applying to this position. These may be uploaded directly to the application or sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line. Instructions to upload documents: Login to your account via jobs.ornl.gov View Profile Under the My Documents section, select Add a Document Contact Information For technical questions, contact: Massimiliano Lupo Pasini (lupopasinim@ornl.gov) Alex Plotkowski (plotkowskiaj@ornl.gov) For application assistance, email: ORNLRecruiting@ornl.gov Security, Credentialing, and Eligibility Requirements This position requires the ability to obtain and maintain an HSPD-12 PIV badge and a Real ID compliant form of identification. Employment is contingent upon successfully completing a Federal Tier 1 background investigation, including declaration of illegal drug activities within the last year, including marijuana and cannabis derivatives under federal law. For foreign national candidates: Candidates who have not resided in the U.S. for three consecutive years are not eligible for a PIV credential and must obtain a favorable Local Site Specific Only (LSSO) risk determination Once the residency requirement is met, a PIV credential will be required Benefits ORNL offers competitive pay and benefits programs, including: Medical, dental, and vision plans Prescription drug coverage 401(k) retirement plan Life insurance and pet insurance Generous vacation and holidays Parental leave Legal insurance with identity theft protection Employee assistance plan Flexible spending and health savings accounts Wellness programs Educational assistance Relocation assistance Employee discounts On-site fitness, banking, and cafeteria facilities Additional Information This position will remain open for a minimum of five (5) days and will close once a qualified candidate is identified and/or hired. Accepted file formats: Word (.doc, .docx), Adobe (.pdf), Rich Text (.rtf), and HTML (.htm, .html), up to 5MB in size. Resumes from third-party vendors will not be accepted. Equal Opportunity Statement 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. If you apply for this position please say you saw it on Physicaloxy

Location: Oak Ridge, TN, US 37830
Company: Oak Ridge National Laboratory
Requisition ID: 15527

Overview

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.

The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods to advance multi-scale coupled physics simulations in support of the missions and programs of the US Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s leadership class Computing Facilities (LCFs).

The successful candidate will demonstrate strong expertise and skills in computational materials, data analytics, development of surrogate and generative DL models, high-performance computing (HPC), and computational sciences.

Major Duties and Responsibilities

Participate in:
- Design and implementation of scalable DL algorithms for atomistic materials modeling applications
- Design and architecture of integrated, hybrid, atomistic simulation software packages (e.g., LAMMPS) and DL models
- Documentation, verification and validation, and software quality activities
Author peer-reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences
Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research in support of the Laboratory’s missions
Engage with the broader DL community to develop and apply scalable physics-informed DL techniques to application areas of interest to the CCP group
Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service
Promote equal opportunity by fostering a respectful workplace in how we treat one another, work together, and measure success

Basic Qualifications

A PhD in materials science, applied mathematics, computer science, or an AI-related field completed within the last 5 years
Demonstrated expertise in atomistic materials modeling for organic, inorganic, and/or hybrid compounds
Demonstrated experience with open-source classical molecular dynamics software LAMMPS
Demonstrated expertise in writing advanced software in Python
Demonstrated experience with the LINUX operating system, LaTeX, Git, Python
Demonstrated expertise in the design and implementation of deep learning algorithms in PyTorch
Expertise in object-oriented programming and scripting languages
Parallel algorithm and software development using the message-passing interface (MPI), particularly as applied to AI/ML algorithms
Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills

Preferred Qualifications

Experience working in a multi-disciplinary research environment that follows modern software quality standards (version control, unit testing, continuous integration, etc.)
Experience in the development of large-scale physics simulation codes, including computational scaling and efficiency, for hybrid exascale supercomputing systems
Programming model experience for multicore and heterogeneous architectures such as graphical processing units (GPUs)
Motivated self-starter with the ability to work independently and 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 adapt to ever-changing needs

Appointment Terms

Applicants cannot have received their Ph.D. 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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Application Instructions

Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application.

Please submit three letters of reference when applying to this position. These may be uploaded directly to the application or sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents:

Login to your account via jobs.ornl.gov
View Profile
Under the My Documents section, select Add a Document

Contact Information

For technical questions, contact:

Massimiliano Lupo Pasini (lupopasinim@ornl.gov)
Alex Plotkowski (plotkowskiaj@ornl.gov)

For application assistance, email: ORNLRecruiting@ornl.gov

Security, Credentialing, and Eligibility Requirements

This position requires the ability to obtain and maintain an HSPD-12 PIV badge and a Real ID compliant form of identification. Employment is contingent upon successfully completing a Federal Tier 1 background investigation, including declaration of illegal drug activities within the last year, including marijuana and cannabis derivatives under federal law.

For foreign national candidates:

Candidates who have not resided in the U.S. for three consecutive years are not eligible for a PIV credential and must obtain a favorable Local Site Specific Only (LSSO) risk determination
Once the residency requirement is met, a PIV credential will be required

Benefits

ORNL offers competitive pay and benefits programs, including:

Medical, dental, and vision plans
Prescription drug coverage
401(k) retirement plan
Life insurance and pet insurance
Generous vacation and holidays
Parental leave
Legal insurance with identity theft protection
Employee assistance plan
Flexible spending and health savings accounts
Wellness programs
Educational assistance
Relocation assistance
Employee discounts
On-site fitness, banking, and cafeteria facilities

Additional Information

This position will remain open for a minimum of five (5) days and will close once a qualified candidate is identified and/or hired.

Accepted file formats: Word (.doc, .docx), Adobe (.pdf), Rich Text (.rtf), and HTML (.htm, .html), up to 5MB in size. Resumes from third-party vendors will not be accepted.

Equal Opportunity Statement

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.

If you apply for this position please say you saw it on Physicaloxy

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