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, parallel storage systems and scientific data management. Recent research project details and outcomes can be found in computer systems conference proceedings, such as HPCA, FAST, SC, DSN, HPDC, IPDPS, and
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models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi-modality data analysis (e.g., image
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of interpretability methods to ensure ML outputs are meaningful in scientific contexts. Preferred: Background in biomedical data, healthcare, or AI for life sciences. Experience with parallel computing. Familiarity
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. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming
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team of undergraduate/postgraduate researchers. Candidates should be able to multitask parallel evolution experiments with phenotypic and genomic analyses. Job Duties and Responsibilities: Typical tasks
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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the collective behavior of complex systems, understanding how micro- level interactions drive macro-level evolution. Practical experience with high-performance computing (HPC) and parallel processing to enable
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approaches in a coherent framework. Rather than treating these disciplines in parallel, Brown PPE emphasizes methodological integration — reconnecting traditions that once addressed questions of justice
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for massively parallel computers. Experience with quantum many-body methods. Preferred Qualifications: A strong computational science background. Familiarity with coupled-cluster method. Understanding