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of the next generation of multiple-criticality control architectures will allow almost unlimited off-board computational power to be used to optimise operational decision-making in near to real-time
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-tier venues (e.g., ICSE, ASE, TOSEM, AAAI, EMSE), with at least 10+ publications, including multiple CORE A/A* papers. Demonstrated expertise in deep learning architectures, computer vision, and medical
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(usually PhD). The Chair of Adaptive Dynamic Systems conducts research in the fields of reconfigurable computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and
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for treating brain disorders? In this PhD you will work with datasets of neuronal activity in animals and humans. You will apply computational approaches to describe spatial and temporal patterns across
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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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for long-term roadmap development. Job Requirements: MSc or PhD in Electrical Engineering, Electronics Engineering, AI, Chip Design, Computer Science, Cybersecurity, or a related field Proven experience with
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to non-technical stakeholders. Specific Requirements Essential Criteria A PhD in Computer Science or a closely related discipline, in a topic directly relevant to video and/or AI. At least 8 years directly
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and
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individuals applying innovative comparative genomics approaches, leveraging long-read sequencing technologies and pangenomic concepts, to better understand the genomic architecture of complex traits, disease
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- the School of Innovation & Technology (SIT) the School of Design, the School of Fine Art and the Mackintosh School of Architecture. The School of Innovation and Technology combines academic study at