42 computer-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Mathjobs" Postdoctoral positions at Argonne
Sort by
Refine Your Search
-
camera technology and multiplexed readout systems for quantum information science applications. In this role, you will join a multidisciplinary team spanning several Argonne divisions and contribute
-
The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
-
ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
-
, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
-
at the Large Hadron Collider (LHC). The successful candidate will contribute to a broad research program that includes physics analysis, detector performance studies, experiment operations, and upgrade
-
. The candidate will assume a primary role in spearheading the development of a comprehensive growth, synthesis, and innovative characterization experimental program specifically tailored to diamond
-
nitrogen-vacancy (NV) diamond quantum magnetometry for high-energy physics experiments. The HEP Division performs cutting-edge research leveraging advanced detector development, high-performance computing
-
completed within the last 0-5 years)in chemical engineering, materials science, industrial engineering, or related fields. Knowledge of Python, JavaScript, Microsoft Excel and other computer programming
-
Position Overview We are seeking a Postdoctoral Appointee to join the Computational Science and Artificial Intelligence Group in the X-ray Science Division of the Advanced Photon Source (APS
-
together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning