28 machine learning Postdoctoral positions at Argonne

Postdoctoral Appointee – Machine Learning for Power Systems

in modeling, analysis and control of electric power distribution and transmission system, applying state of the art machine learning (ML) and deep learning algorithms to develop cybersecurity

Postdoctoral Appointee -- Physics-Informed Machine Learning/Hydrology

Argonne National Laboratory, a U.S. Department of Energy National Laboratory, has an opening for a Postdoctoral Appointee specialized in physics-informed machine learning at the Department

Postdoctoral Appointee - Hydrology/Machine Learning

for machine learning/AI model development development using Pytorch, Tesnor Flow or similar platforms. Utilization of high-performance computational platforms. Writing and modifying scientific code in Fortran/C

Postdoctoral Appointee – Machine Learning for Power System

of the art machine learning and deep learning algorithms to develop cybersecurity, optimization, and control solutions for transmission and distribution system operators. Job duties but not limited to: Develop

Postdoctoral Appointee - Machine Learning for X-ray Imaging

The X-ray Imaging group (IMG) of the Advanced Photon Source (APS) is currently seeking a postdoc with expertise in machine learning (ML) and image processing to develop cutting edge processing

Postdoctoral Appointee - NST - Machine Learning for Electronic Structure and Materials Modeling

of machine learning in electronic structure calculations and advanced sampling. The postdoctoral researcher will work within the groups of Professor Giulia Galli (https://galligroup.uchicago.edu/ ) and Dr

Postdoctoral Appointee – Machine Learning for X-ray Science

position to develop and apply machine learning algorithms and approaches for x-ray science and instruments. These machine learning methods will be integrated into a shared platform that will lower

Postdoctoral Appointee - Machine Learning for Tuning of Radioactive Beams

Appointee position planned to start around March-April, 2024. The successful candidate will be primarily working with physicists and computer scientists in the development of an automated machine-learning (ML

Postdoctoral Appointee – Differentiable and Portable Linear Solvers

, respect, integrity and teamwork. Desired skills and qualifications: Experience with automatic differentiation and generation of derivatives. Experience with machine learning methods. Job Family Postdoctoral

Postdoctoral Appointee – Low-Carbon Fuel Sprays and Engine Combustion Modeling

multidisciplinary team comprised of fellow postdoctoral appointees and staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance