140 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
, and compliance requirements. Strong aptitude for computer systems, electronic tools, and digital workflows. Ability to learn and adapt to new technologies, including AI-enabled tools used to support
-
modeling, multiscale approaches) to support materials development and manufacturing process understanding. Use AI, machine learning, and data-driven methods as enabling tools to accelerate experimentation
-
, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
-
modeling, machine learning, and automated experimentation. Mentor and support Group Leaders to ensure excellence in research performance, staff development, inclusion, and cross‑disciplinary collaboration
-
toward integration of hydropower with battery storage and other technologies. Computational and analytical skills : Demonstrated ability in selecting and deploying machine learning tools (Random Forest
-
, assessing hazards for every task, and committing to continuous learning. Other tasks as assigned by management. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values
-
work to exciting research in multi-disciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and machine learning skills to bear as you develop new methods
-
, JAX etc.) Two or more years of experience in applying machine learning methods for instrument control, such as on a microscope, or on a nanomaterials synthesis platform resulting in publishable
-
advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
-
physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team