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of cluster and job/resource management software (e.g., Warewulf, Slurm, XCat) Parallel and distributed file system (Lustre) experience is a plus Experience with the installation, configuration and
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Qualifications Experience: Relevant programming experience developing, implementing, debugging, and maintaining applications with Python. Experience working with high performance computers (e.g., parallelizing and
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State University of New York University at Albany | Albany, New York | United States | about 10 hours ago
vibration isolation). In parallel to the benefits of quantum computing, artificial intelligence and neuromorphic computing seek to emulate the massively parallel, highly efficient computing capacity
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at least one of: High-Performance Computing Distributed Systems Parallel Computing High Performance Algorithms Multiple Linux distributions · Experience with SLURM or similar HPC schedulers
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software packages. Familiarity with core data structures, algorithms, and some exposure to parallel or distributed computing. Strong quantitative and critical-thinking abilities demonstrated through
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including workload schedulers, storage systems, and distributed compute nodes. Applies analytical methods to evaluate system performance, identify bottlenecks, and implement corrective actions to improve
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tools (OpenXDMod), distributed and parallel file systems (CEPHFS, NFS, Lustre, BeeGFS), and virtualization platforms (Openstack) Rewards and Benefits This position is located in Ithaca, New York
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of computational computing clusters including, but not limited to GPU clusters, General HPC clusters, and SMP environments. Experience with Centos or similar Linux distributions. Experience with programming jobs
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, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed tomography scans. Aid dental students, residents and/or faculty in four-handed dentistry and in routine chair
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of relevant experience in Linux systems administration or HPC systems engineering. Preferred Qualifications Demonstrated experience leading the design and deployment of HPC or large-scale distributed computing