Military Science Modeling Simulation Jobs in Oak Ridge, TN

Requisition Id 16307 

Overview:  

We are seeking an Associate R&D Staff Member in Data Science for Advanced Manufacturing who will focus on the development of next-generation, data-driven manufacturing systems that integrate artificial intelligence, real-time sensing, and digital twins to transform how critical components are designed, produced, and qualified. The selected candidates will conduct research in data science and AI to develop scalable, deployable methodologies to assess and to improve manufacturing quality, efficiency, and certification readiness. This position resides in the Manufacturing Systems Analytics group in the Digital and Secure Manufacturing Section, Manufacturing Science Division, Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL).

You will work at the MDF to advance digital manufacturing technologies and to accelerate their deployment to industry and national scale applications. The MDF hosts a diverse set of advanced manufacturing systems - including powder bed, directed energy deposition, machining, polymer, and convergent manufacturing systems – used to produce critical components from advanced materials.

These systems are instrumented and connected through a unified digital thread platform that captures multimodal, high-frequency data across the full manufacturing lifecycle, from process execution to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization.

In this role, you will leverage large-scale, heterogeneous datasets to develop and deploy AI-driven methods for:

1. Real-time quality monitoring and control of manufacturing processes
2. Understanding relationships between manufacturing intent, machine behavior, and part performance
3. Optimization of manufacturing processes for improved throughput, reliability, and quality
   

You will contribute to the development of integrated data and AI workflows that span data acquisition, modeling, and decision-making, including deployment at the edge and across distributed systems. You will have access to extensive experimental and computational resources and will be expected to publish research, present results, and contribute to high-impact programs. With over 100 manufacturing systems at the MDF, this role offers the opportunity to work on diverse, high-impact problems and to shape the future of intelligent manufacturing.

Major Duties/Responsibilities: 

• Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal manufacturing datasets, including sensor streams, in-process signals, post-process characterization data, simulation outputs, and digital twin data.
• Design and implement scalable data engineering pipelines for ingestion, transformation, validation, and curation of manufacturing data, enabling high-quality, AI-ready datasets. Develop, integrate, and evaluate AI/ML models for anomaly detection, predictive modeling, process optimization, and automated decision support, including real-time and edge deployment
• Contribute to the development of software tools and workflows for processing and analyzing manufacturing and characterization data
• Develop and integrate imaging and sensing systems for data collection and monitoring
• Develop modular, extensible workflows (e.g., service-oriented or agent-based architectures) to orchestrate data processing, simulation, and decision-making
• Publish research results in peer reviewed journals and present findings at scientific conferences
• Mentor students and junior staff
• Collaborate with multidisciplinary teams to provide computational and analytical expertise across projects
• Support broader research and development activities within the MDF
• Contribute to proposals, publications, and cross-organizational collaborations to advance digital manufacturing research
• 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:

• Ph.D. in mechanical engineering, material science, electrical engineering, computer engineering, computer science, data science, applied mathematics, or a closely related field
• Demonstrated experience applying data analytics, statistical modeling, and machine learning to real world datasets.
• Experience conceiving and executing research and development projects
• Proficiency in Python and common data science and machine learning libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow)
• Experience developing and deploying machine learning or deep learning models
• Experience building and maintaining data processing pipelines for structured and unstructured data
• Familiarity with high-performance computing, cloud environments, or distributed data systems
• Familiarity with uncertainty quantification methods in AI/ML
• Ability to present complex results to multidisciplinary teams, including engineering, scientific, and operational stakeholders
• Ability to work effectively in a dynamic, collaborative research environment
• Excellent verbal and written communication skills

Preferred Qualifications:

• Experience working with manufacturing, materials, and sensor data
• Experience with real-time or streaming data systems and edge AI deployment
• Experience with multimodal datasets (e.g., imaging, time-series, and process data)
• Experience with API-based data services, workflow automation, or integration of analytics into production systems
• Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies
• Experience collaborating across national laboratories, academia, or industry in multidisciplinary teams
• Excellent written and oral communication skills.
• Motivated self-starter with the 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 adapt to ever changing needs.

Special Requirements:

• Visa sponsorship is not available for this position
• This is a temporary 24-month position. 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.
• Three letters of reference are required.

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to ORNLRecruiting@ornl.gov with the position title and number referenced in the subject line.

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

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.

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.

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.

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.