Sort by
Refine Your Search
-
computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient
-
. The goal of this work is to investigate the dynamics of beams with intense space charge and benchmark simulation models against experimental results. As a U.S. Department of Energy (DOE) Office of Science
-
, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible
-
research analysis on geothermal well development and other advanced energy technologies that could achieve transformative gains in energy efficiency. Ability to develop optimization and life cycle models
-
to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
-
or machine learning potentials (iv) modeling of the solid and aqueous interfaces. Research proposal or concept writing experience. Programming experience for workflow development and scientific computing
-
Plant Phenotyping Laboratory (https://www.ornl.gov/appl ). Perform phenotypic characterizations of transgenic and genome-edited lines in poplar and other model or bioenergy plants Perform molecular and
-
Qualifications: Ideal candidates will possess a background in nuclear engineering. Previous experience using thermal hydraulics models and codes Previous experience using the MOOSE framework. Familiarity with
-
Substantial programming skills using Python or modern C/C++ Experience with machine learning and deep learning libraries Experience building AI models in platforms such as TensorFlow, Keras, or PyTorch