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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
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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
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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
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to contribute to both the scientific and technical aspects of the ATLAS program in a highly collaborative research environment. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years
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, 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
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Directed Research and Development (LDRD) project. This research focuses on understanding how critical elements are distributed at mineral-water interfaces, with the goal of revealing the fundamental chemical
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execution environments, or secure enclaves. Experience with distributed computing, cloud computing, containers, Kubernetes, Docker, Apptainer/Singularity, or high-performance computing environments
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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
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initiatives, providing valuable insights to peer reviewers and program managers alike. Position Requirements Required skills and qualifications: Recently completed PhD within the last 0-5 years in an applicable
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, or network-based modeling of infrastructure or industrial systems. Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization