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Field
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partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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involve working closely with teams conducting parallel work with preschool children and adolescents within the ‘All About Me’ project. What We Offer As an employer, we genuinely care about our employees
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learning frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience inscalable data processing, including the use of parallel computing, cloud platforms,and distributed systems
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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content moderation framework for immersive 3D virtual environments, such as Roblox and Minecraft. The engineer will play a key role in building a parallelized, agent-driven exploration system and
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process information to generate perception, form memories and guide behaviour. Developed through the vision and partnership of the Gatsby Charitable Foundation and Wellcome, and with substantial investment
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on competence: contributing to research software development supporting simulations and/or data workflows (HPC/parallel environments), and open/reproducible release of data and analysis scripts under FAIR
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' parallel to research education, in which artistic practice should be the core of the doctoral work. At the same time, artistic practice must be followed by an explicit reflection which, in the presentation
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate