Applied Data Scientist - Staff Member

Requisition Id 16760 

Overview:  

We are seeking an Applied Data Scientist to perform development of novel and advanced AI/ML algorithms. This work will support a broad user base by applying AI methods that span low-power edge computing utilizing spiking neural network algorithms to large models utilizing agentic AI to solve complicated problems in nuclear safeguards, warhead monitoring and fundamental physics. Experience with sensor modalities such as radiation detectors, event-based cameras and seismo-acoustic sensors is needed. This role resides in the Advanced Detection and Applied Data Science (ADADS) group, Nuclear Structure & Advanced Technologies Section, Physics Division, Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL).

ADADS draws from fundamental physics to develop technologies and processes that support the design, development, and deployment of high-sensitivity detection systems for measuring radiation and other physics phenomenologies. The group focuses on the development and evaluation of novel and advanced radiation detector and non-destructive evaluation concepts for basic science, nonproliferation, national security, and intelligence organizations. The ADADS group performs the research and technology development to evolve these advanced concepts from conception to demonstration or deployment with particular emphasis on sensitivity and specificity in actual field operations, including use of radiation transport codes to model these systems and analysis codes to isolate signals of interest.

Major Duties/Responsibilities: 

In this role, you will work with and support research staff within ADADS and throughout ORNL to develop and apply modern data science/machine learning techniques to a wide variety of subjects including the characterization of nuclear material and nuclear facility operations, as well as more fundamental physics research. The research involves development and testing of novel data analytics processes and specialized methods to improve measurement fidelity and reduce uncertainties in models used for real-world decisions. Results will be documented by publication in high impact papers, journals, conference papers and technical reports. The work will involve collaboration in a team environment performing project work and developing research proposals.

Basic Qualifications:

• Bachelor’s degree in physics, computer science, mathematics, or a related field
• A minimum of 5 years of experience, post bachelor’s, demonstrating capabilities and experience in data science or data analytics
• Ability to obtain and maintain a clearance from the Department of Energy

Preferred Qualifications:

• Basic understanding of the detection of radioactive materials through measurement of ionizing radiation
• Experience with applications in nuclear non-proliferation and fundamental physics
• Experience in one or more of the following ML research areas:
  • Neuromorphic computing
  • Uncertainty quantification
  • Unsupervised/Semi-supervised learning and data mining techniques (clustering, embeddings, dimensionality reduction, anomaly detection)
  • Physics informed machine learning
• Practical experience using ML models:
  • Dataset curation and preprocessing
  • Applications leveraging off-the-shelf ML models
  • Fine-tuning pre-trained models for specific tasks
  • Designing and training models, from scratch
• Familiarity with relevant technologies such as:
  • Computer programming languages such as Python, JavaScript, FORTRAN, C, and C++
  • Machine learning libraries such as Pytorch, TensorFlow, Scikit-Learn, and OpenCV
  • 3D game development software such as Unity including VR/AR packages
• Commitment to stay current with modern data analytics/machine learning trends
• A strong interest in problem solving and applying new skills and methods
• Excellent human relation and oral and written communication skills and a demonstrated ability to work in a team-oriented environment with a broad range of domestic or international collaborators
• Ability to work both independently, with minimal supervision, or as an effective member of an agile development team
  

Special Requirements: 

• Visa sponsorship is not available for this position.
• 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 (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.
  
  

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.

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.