44 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" research jobs at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
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
-
computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
-
to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
-
Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
ML concepts and architectures and hands-on experience with open-source AI/ML packages (such as pytorch, scikit-learn, tensorflow, JAX etc.). Preferred Qualifications: Good grasp of concepts in solid
-
Expertise in machine learning and big data analysis Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to participate creatively in collaborative
-
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
-
to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
-
of agentic AI for science, scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models, in the context of leadership scientific workflows and
-
electronic structure theory (e.g., density functional theory), and machine learning based computational studies of molecular and periodic systems. The postdoc will also work within a multidisciplinary multi