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to solve challenging problems in the microelectronics area. Note: Synthesis of bulk materials, first-principles simulations/modeling, and organic or bio-related areas are not in consideration
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focus will be on exploring the utility of artificial intelligence models in the study of the above, studying quantum mechanical generalizations, and uncovering connections to statistical models. Position
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The Environmental Science Division at Argonne National Laboratory is seeking a postdoctoral researcher to join a project aimed at improving model representations of carbon cycling and greenhouse gas
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Energy Systems and Infrastructure Analysis Division. We are seeking applicants with a strong technical background and expertise in international trade modeling, particularly in the upstream automotive
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, and optimize for energy efficiency HPC applications and high performance data stream analytics workloads. Use of novel accelerator designs, and automatic methods to model/predict how performance would
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, and spatial transcriptomics. Key responsibilities include: Developing AI/ML methods for image alignment across modalities Automated feature detection Predictive modeling of vascularization patterns
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techniques to enable multimodal online monitoring of chemical and radiochemical separations processes Acquire fundamental data relevant to chemical separations in support of related modeling efforts Analyze
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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-ion battery operation, cathode materials, and degradation mechanisms Excellent written and oral communication skills and the ability to work collaboratively in a team environment Ability to model
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symmetries tests and to probe the realm of physics beyond the Standard Model. We aim to appoint at the rank of Assistant Physicist (equivalent to a tenure-track Assistant Professor), with a start date as early