63 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work
-
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
-
applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis 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
-
computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
-
computing environments. Interest or experience in machine learning, inverse problems, or AI for scientific data. Strong record of research productivity and ability to work effectively in a collaborative
-
Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
that can incorporate multi-scale computational simulations to aid with data fusion across multiple modalities of experiments with the final goal of discovering novel materials phenomena or even new materials
-
-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery
-
, dimensionality reduction, embeddings, etc.). Understanding of computational scaling techniques for machine learning and high-performance computing. Preferred Qualifications: Expertise in foundational models and
-
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