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Field
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Center for Scientific Computing (sciCORE). We seek candidates with an outstanding research record in distributed data and knowledge engineering, in particular in one or several of the following areas
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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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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, optimize, and support AI/ML pipelines on HPC and GPU-accelerated systems. Optimize large-scale training and inference workflows using distributed computing frameworks and performance analysis tools
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work. Essential Job Duties: Software Development & Reliability Engineering : Design and develop software for operating and scaling a distributed network of AI-enabled edge computing nodes, growing from
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programming languages (such as Python or Java) and SQL, and use of distributed computing frameworks such as Apache Spark; delivery of solutions on cloud-based data engineering platforms (e.g
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programming languages (such as Python or Java) and SQL, and use of distributed computing frameworks such as Apache Spark; delivery of solutions on cloud-based data engineering platforms (e.g
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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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computing with CUDA/SYCL, MPI, Krylov solvers Preferred knowledge: Distributed preconditioners (BDDC, GDSW), CI/CD, collaborative software development. The group is situated in the new TUM Campus, in
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technologies that enable reliable, automated execution of scientific applications across heterogeneous, geographically distributed computing environments, integrating compute, storage, networking, and