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manage large-scale HPC storage systems, including parallel file systems such as Lustre, GPFS/Spectrum Scale, BeeGFS and WEKA. Design, implement, and operate large-scale Ceph storage clusters for HPC and
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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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metabolism change, paralleling their locomotion in the gut, (ii) Ascaris suum L3 larvae use different metabolic pathways in distinct body regions, (iii) with Artemisinin derivatives not interfering with
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well as national and international collaborators. This British Heart Foundation-funded project, based in the Fuller Lab, will develop parallel, novel strategies targeting Ca(v)1.2 for translation into new
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microbiome. This work involves the use of parallel plating in microtiter wells of combinations of nutrients and bacterial cells, using multiplate readers. This research assistantship is intended for a Rutgers
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. (2020) Epithelial–mesenchymal plasticity: emerging parallels between tissue morphogenesis and cancer metastasis. Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 375, No. 1809
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analysis environment. ● Experience with data processing at scale, and an understanding of which tools are appropriate at which times. ● Working knowledge of OpenMP, MPI or other parallel processing
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/Fortran) Shared and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Machine Learning libraries such as Tensorflow or PyTorch Serial and parallel
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collaborative, cutting-edge research at the forefront of modern biology. Specific tasks include being trained for and performing a technique newly developed in the Greenleaf lab - massively parallel filter
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of the human microbiome. This work involves the use of parallel plating in microtiter wells of combinations of nutrients and bacterial cells, using multiplate readers. This research assistantship is intended