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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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-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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specifically, you will be in charge of: Conducting advanced research on next‑generation wireless networks, with a focus on high‑performance and reliable communication over unlicensed spectrum. Designing and
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the role of hyperglycosylated extracellular matrix (ECM) in the tumor growth and its role in promoting EMT. The selected candidate will perform experiments in vitro and in vivo, using high-throughput
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“Multiprofessional Center for Paralympic and Parasport Studies (CMEPP): Health, Education, High Performance, and Technology”, one of the Science Centers for Development (SCDs) supported by FAPESP. Prerequisites: • PhD
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processing, while maintaining high efficiency and selectivity in flotation performance. Responsibilities: Develop and synthesize bio-based flotation additives (e.g., collectors, dispersants, depressants
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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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for viability in these cohorts subject to high mortality rates could compensate for the low number of individuals by leaving only those of very good quality with strong phenotypic and demographic performance
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, Computer Science, or related disciplines. Knowledge and Professional Experience: · Knowledge of programming languages used in data analysis (particularly python) is strongly recommended. · High Performance