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Field
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-solving, and collaborative mindset Highly desirable Experience with distributed training or ML systems Knowledge of privacy-enhancing technologies and parallel programming Experience with multilingual AI
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are searching for a motivated and talented Computer Science and Software Engineer to join our Applied Communications team of the Applied Research Laboratory (ARL) at Penn State. This is a software engineering
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simulated and measured results to assess quantities of interest. Interface with world-class exascale computing clusters. Work with a dynamic team of researchers, developers, experimentalists, and model
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description UiB - Knowledge that shapes society UiB shall be among Europe's
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in deep learning at scale, familiarity with the “alphabet soup” of distributed computing (DP, TP, SP, CP, EP) Experience with production environments, including Git-based workflows Experience working
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opportunity to collaborate together and learn methods from the parallel project, building a broad skillset. Both positions are part of the larger project “Bringing the wild into the lab with Virtual Reality
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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computational approaches, including in vivo Massively Parallel Reporter Assays (MPRAs), to define the sequence basis and functional consequences of enhancer activity and to expand MPRA-based approaches to other
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environments, parallel and distributed file systems, tiered storage strategies, and hybrid cloud integration. Strong communication skills across technical and non-technical audiences Strong understanding
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Qualifications Experience: Relevant programming experience developing, implementing, debugging, and maintaining applications with Python. Experience working with high performance computers (e.g., parallelizing and