-
The High Energy Physics Division (HEPD) at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML
-
position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
-
and applying algorithms and software for the use of first principles and atomistic modeling, together with machine learning, to accelerate the inversion of experimental characterization data
-
to the development of x-ray cavity alignment procedures – with application of machine learning tools in particular. Contribute to R&D activities for realization of the real full fledged CBXFELs (beyond the test
-
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
-
position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
-
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
-
application. In your cover letter, please describe your previous experience with materials microscopy simulation/analysis; describe your experience with machine learning/computer vision; describe your software
-
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
-
, respect, integrity, and teamwork. Desired skills and qualifications: Expertise in computer science, supercomputing, machine learning, AI. Application materials required: Upon submitting your application