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and Eligibility Applications will be accepted from January 7, 2026, March 1, 2026, for one position starting as early as May 4, 2026. This position will support one postdoc for two years. You must first
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properties of the above materials. Collaborate with ORNL postdocs and staff who are involved in structural characterization. Participate in the development of new ideas and projects. Present and report
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Requisition Id 15880 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. We are seeking an outstanding Postdoctoral...
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming
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RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent written and oral communication skills. Motivated self-starter with
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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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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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(Xilinx Vitis/Vivado, Intel Quartus, HLS tools) HPC environments or GPU-accelerated computing On-detector firmware or data acquisition systems Familiarity with HEP data formats and reconstruction