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to closely collaborate with CS faculty members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience
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guidance of two experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing: Dr. Min Xu – Affiliated Associate Professor
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: Experience with CUDA programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high
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optimization, intelligent runtime systems, code generation and transformation, HPC, parallel and distributed computing, compiler infrastructures, heterogeneous systems, and autonomous system optimization
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developing and managing automated and parallel scientific workflows , including task execution systems, dependency management, and pipeline execution on distributed computing resources. Experience with HPC
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workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data
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distributed computing runtime with application and compilers to efficiently integrate quantum processors with HPC resources. The research will explore different quantum computing modalities, their
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optimization fundamentals, both computational and mathematical. Preferred Qualifications Familiarity with distributed computing frameworks such as MPI and OpenMP Experience with Pyomo and/or JuMP Experience
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systems for extreme-scale, heterogeneous computing. This role sits at the intersection of compiler infrastructure, formal verification, runtime systems, and hardware/software co‑design—expanding into
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systems for extreme-scale, heterogeneous computing. This role sits at the intersection of compiler infrastructure, formal verification, runtime systems, and hardware/software co‑design—expanding into