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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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-machine system interactions. The project seeks to identify key mechanisms affecting transient stability and to provide modelling and analysis tools that support robust control and protection design for
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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
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quantum chemistry (DFT) and control engineering. PhD position in chemical reaction engineering (Kinetic modeling & thermal runaway) Supervisors: Sébastien Leveneur (sebastien.leveneur@ircelyon.univ-lyon1.fr
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Scientific Area of Systems, Decision and Control Scholarship Theme: Computational Auditory System Simulators and Machine Learning-based Optimisation
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) that optimise TST properties for neuromorphic computing. The outcome is a validated VMD pipeline that identifies candidate materials and provides concrete, model-based prescriptions for tuning their behaviour
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LES resolved wake dynamics and the coupling to aero-elastic models and wind turbine control. You will be a member of the Fluid and Offshore Mechanics section, which has a strong track record in offshore
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The research associate will focus on Vision-Language Model based situation awareness and decision-making