46 parallel-and-distributed-computing-"Computer-Vision-Center" Postdoctoral positions at Argonne
Sort by
Refine Your Search
-
Argonne National Laboratory’s Materials Science Division (MSD) invites applications for a Postdoctoral Appointee in computational materials chemistry and atomistic modeling to investigate
-
The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to conduct computational research focused on transition metal-containing clusters
-
The Data Science Learning division is seeking a postdoctoral researcher to develop and apply artificial intelligence and computational biology methods to investigate the molecular and cellular
-
The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
-
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
-
(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
-
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
-
experiment or another collider-based high-energy physics experiment Experience with silicon detectors, Trigger/DAQ systems, or detector operations Experience in software and computing, including distributed
-
execution environments, or secure enclaves. Experience with distributed computing, cloud computing, containers, Kubernetes, Docker, Apptainer/Singularity, or high-performance computing environments
-
develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running