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Field
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simulations on High Performance Computing, the ability to analyze and organize large datasets or model outputs, knowledge of Unix/Linux, and experience with commonly used software and protocols in
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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-temperature and/or high-pressure power cycles and/or components, or sCO2 cycles and/or components thermal processes or high-pressure systems High-Performance-Computing Software toolset development Research
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experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core
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—are especially encouraged to apply. The ANL ATLAS group maintains strong involvement across the experiment, including detector operations, TDAQ upgrades, Software and Computing, ML development, and High
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RNA-seq, ATAC-seq, and ChIP-seq. Experience in working with high-performance computing environment. Experience in data management and developing data-processing pipelines. Proficiency in programming
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-performance computing to deliver fast, accurate, and accessible forecasts for monitoring, reporting, and verification (MRV) of geochemical CDR. The overarching goal is to improve understanding and
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infrastructure, core lab funding, and Advanced ERC grant funding Extensive collaborative opportunities with other lab members, labs, and institutes High-performance life sciences and compute infrastructure with
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, Computer Science, or a closely related field. Experience in at least one of the following areas: FPGA programming (VHDL/Verilog, HLS) Pixel detectors in high-energy physics or radiation detection
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. Data Acquisition & Analysis: Captures high-resolution live calcium imaging data using advanced microscopy systems. Applies computational tools and algorithms to analyze calcium signaling patterns and