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Field
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using
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human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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templates and processes for scaling up the grant writing and fundraising support capabilities for multiple companies and/or BMDC in parallel. Develop a library of templates, awarded proposals and strategy
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-focused clinics we offer an inter-disciplinarily approach to patient care that provides access to the most current therapies and to the resources of the University. In parallel with our clinical activities
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We
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duties. Ability to effectively manage time and see assigned parts of projects through to completion on deadline. Proven ability to juggle multiple related projects in parallel with concurrent and staggered
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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2025 - 23:59 (UTC) Type of Contract Permanent Job Status Not Applicable Hours Per Week See description Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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cutting-edge requirements into resilient and scalable systems. The successful candidate will serve as a trusted technical advisor, systems architect, and subject matter expert across multiple classified HPC