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The project: The domain of High Performance Computing (HPC) effectively utilises massively multicore computers that facilitate the distribution of scientific workloads across thousands of compute
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through sensitivity, uncertainty, and scalability analyses. – Enhance the computational efficiency of large-scale optimization problems by exploring decomposition techniques, parallelization, and
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vendors, each with their own management interfaces, data formats, and access restrictions. In parallel, AI-driven services are increasingly deployed in a distributed fashion, with inference spread across
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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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to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will develop a novel hierarchical control framework
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Engineering, Applied Physics, Applied Mathematics, Computer Science/Engineering, Geomatics, or a related field. You have knowledge of distributed, parallel, and high-performance computing suitable for handling
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). Strong academic background and competencies in parallel programming, distributed computing, and performance engineering. Familiarity with accelerator programming (e.g, GPU), hardware programming, high
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you an engineer who wants to contribute to the high
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between nonlinear dynamics and computing metrics in micro-ring resonators and coupled ring-resonator architectures Evaluate the number and spatial distribution of coupled cavities for photonic reservoir
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circuits for enhancing computing efficiency through parallelism. The PhD student will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15