Applied Data Scientist - R&D Associate

Oak Ridge National Laboratory

Oak Ridge National Laboratory (ORNL) is searching for an Applied Data Scientist to join their Advanced Detection and Applied Data Science (ADADS) group. Located in the Physics Division, this role involves advancing technologies for high-sensitivity detection systems used by organizations focused on national security and intelligence, integrating cutting-edge data science methodologies.

In this role you can expect to have the responsibilities:

• Collaborate with ADADS and ORNL research teams to enhance data science and machine learning techniques for nuclear security missions.
• Develop and test innovative data analytics methods and specialized algorithms to enhance measurement accuracy.
• Document research findings in high-impact journals, conference papers, and technical reports.
• Work in teams to manage projects and craft research proposals.
• Uphold ORNL's mission and core values including Impact, Integrity, and Safety, fostering a respectful workplace.

This role comes with the following benefits:

• Medical and retirement plans
• Flexible work hours
• On-site amenities such as fitness and cafeteria facilities
• Prescription Drug Plan
• Dental and Vision Plans
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life and Disability Insurance
• 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
• Employee Discounts

This role requires you to have:

• PhD in physics, engineering, mathematics, statistics, or a related field.
• At least 2 years of research or laboratory experience.
• Proven experience in data science or analytics.

You would benefit from having:

• Eligibility for Department of Energy clearance.
• Understanding of radioactive material detection using ionizing radiation.
• Experience with languages like C, C++, Python, Julia, or R.
• Knowledge of TensorFlow, OpenCV, and machine learning libraries.
• Expertise in applying machine learning techniques to real-world data.
• Experience with time series data analysis for anomaly detection.
• Experience in data fusion and sensor stream correlation.
• Proficiency in edge computation adaptation and optimization.
• Experience with LiDAR or photogrammetry.

ORNL values diversity and promotes a culture of equal opportunity, ensuring that diverse perspectives and backgrounds are integral to the employment environment. The organization emphasizes integrity, teamwork, and respect in interactions and contributions to the ORNL mission.