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of this Research Fellowship is to contribute to a deeper, theory-driven understanding of the global Earth observation (EO) market and industry, identifying its structural dynamics, competitive landscape and long
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; Experience with general purpose deep learning frameworks, such as Tensorflow or PyTorch; Record of relevant coding experiences relevant to the job description; Experience with HPC tools (e.g., MPI, SLURM, etc
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detection and management, such as code exposure, coverage, and secure patching/update architectures as part of DevSecOps processes; Validating mission data system software interfaces and service-specific
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learning and population coding, to improve neuromorphic system resilience during in-orbit operation. contribute to the establishment of a methodology for evaluating neuromorphic versus traditional AI
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of models from requirements or higher-level models, design optimisation, verification of models; implementation: generation of code for onboard real-time and critical systems, and smart manufacturing