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project reporting and compliance requirements. • Architect and maintain cloud-based ML environments (e.g., Azure, AWS, Databricks) including governance, role-based access control (RBAC), MLOps best
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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learning, generalization/robustness and privacy aspects in scalable learning algorithms. Large‑scale optimization and control: Optimal control, model predictive control and other optimization‑based control
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of control mechanisms and evaluation methods that hold regardless of which underlying TTS technology is used. This is a core requirement in a field where generative AI models evolve rapidly. We
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offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian stochastic models, based on (generalized) Hermite
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to offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian stochastic models, based on (generalized) Hermite
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adaptability of robotic systems. In particular, the research will investigate distributed and/or game-theoretic control frameworks for multi-robot systems, integrating optimization-based planning with learning
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. Analyze coupled failure mechanisms involving heat generation, gas evolution, internal shorting, and structural degradation, and connect them to cell- and pack-level safety performance. Design model-based
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Marie-Skłodowska-Curie Action (MSCA) grant on WindConnect project. The project The WindConnect (wind farm control and integration in sector-coupled power systems https://cordis.europa.eu/project/id
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and the safety implications arising from these interacting processes. You will use and extend PyBaMM, which is an open-source Python-based battery modelling framework (https://pybamm.org