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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE "GUGLIELMO MARCONI" | Italy | about 2 months ago
. This Research Fellow position focuses on deployment methodologies for heterogeneous RISC-V many-core systems using the Deeploy framework, addressing workload partitioning, parallel execution, and communication
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding while maintaining clarity in the interpretation of results. Concurrently, AI-based methods are...
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resources of CESAM, including its Machine Learning and Deep Learning hub, • close collaborations with ONERA. The successful candidate will work in a multidisciplinary environment bringing together researchers
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27 Feb 2026 Job Information Organisation/Company ONERA Department DAAA Research Field Engineering » Aerospace engineering Engineering » Mechanical engineering Engineering » Simulation engineering
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27 Feb 2026 Job Information Organisation/Company ONERA Department DAAA Research Field Engineering » Mechanical engineering Engineering » Aerospace engineering Engineering » Simulation engineering
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involved in the CASSIOPEE project, which brings together 2 academic players (LAM and ONERA) and 2 industrial partners (ALPAO and FLI), to implement an innovative AO system based on state-of-the-art
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for spectral measurements (across different wavelengths of light) of this spatial response, in connection with the development of multispectral and hyperspectral detectors. To address these challenges, ONERA has