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opportunities for a broader range of science-based applications What will I be doing? As a postdoctoral fellow in the FES Postdoctoral Research Program, you will conduct your proposed research related to the FES
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We are seeking a highly motivated and creative candidate for a fully supported postdoctoral fellowship to develop immune-based therapies. Specifically, the research is aimed to develop cell-based immunotherapies for pediatric tumors. Studies are focused on using genetic engineering approaches to...
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workloads. Conduct research on language front‑end abstractions, mixed‑precision modeling, heterogeneous parallelism, and MLIR-level transformations. HPC System Co‑Design: Work with domain scientists and
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detailed information on how to apply for the MLEF program. Application tips can be found on the MLEF website. Application Deadline 1/20/2026 11:59:00 PM Eastern Time Zone Description The U.S. Department
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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adapting large-scale codes developed for parallel computing. Record of excellence in professional achievement, as evidenced by a strong publication record. Demonstrated ability to carry out independent
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initiative are encouraged, research directions will be developed in consultation with the mentor to ensure feasibility and alignment with program objectives. The successful candidate will publish research and
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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The Q-NEXT National Quantum Information Science and Research Center based at Argonne National Laboratory invites applications for a postdoctoral position to conduct research in the field of material
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and