-
Postdoctoral Research Associate - Structural Simulation and Machine Learning (ML) for Polymer Compos
manufacturing technologies through machine learning and physics-based simulations, specifically finite element analysis (FEA) for polymer composites. The candidate will also focus on developing a manufacturing
-
) is seeking qualified applicants for a postdoctoral position in machine learning and surrogate models. Areas of interest include graph neural networks, federated learning, data-driven model reduction
-
Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods
-
research associate who will focus on machine learning, signal processing, and statistical analysis with emphasis on prognostics and applications. This position resides in the Accelerator Science and
-
. The project will focus on research and development of advanced machine learning and deep learning algorithms to analyze large quantities of multimodal images and data arising from the Advanced Plant Phenotyping
-
engineering, applied mathematics, physics, or related field with an evidence of understanding nuclear nonproliferation and/or the nuclear fuel cycle. Experience applying machine learning techniques to problems
-
the Geospatial Science and Human Security Division (GSHSD) at ORNL. The group performs artificial intelligence, computer vision, and federated learning research initiatives, with emphasis on large scale geospatial
-
Requisition Id 12983 Overview: We are seeking a Postdoctoral Research Associate who will focus on developing and applying machine learning algorithms relevant to autonomous experimental laboratories
-
the laboratory Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs Ability to acquire data and control
-
Experience with multi-physics simulations on high performance computing (HPC) and machine learning (ML) Experience working in a multi-disciplinary research environment Demonstrated written and oral