Applied Data Scientist - Staff Member

About the role

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.

Responsibilities

• 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.
• Develop and test novel data analytics processes and specialized methods to improve measurement fidelity and reduce uncertainties in models used for real-world decisions.
• Document results by publication in high impact papers, journals, conference papers and technical reports.
• Collaborate in a team environment performing project work and developing research proposals.

Requirements

• 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

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
• 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
• Able to work both independently, with minimal supervision, or as an effective member of an agile development team

Preferred Qualifications

• 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

Special Requirements

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.