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Description Mathematical modeling forms the basis for understanding, simulating, optimizing and controlling numerous scientific phenomenon and associated measurements. Mathematical models frequently take the
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research related to the application of computational mechanics techniques and numerical simulations for the topology optimization of structures considering a minimum weight approach and advanced constraints
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effect and its great versatility. Indeed, it allows for the designing of a wide variety of materials, and numerous efforts are currently being made to industrialize this process. The objective
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one of the central challenges in quantum machine learning: how to train quantum systems efficiently and reliably on scaling quantum hardware. The research will develop novel optimization frameworks
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Do you have a strong technical background in Machine Learning and Numerical Modelling? Are you interested in working with industry to develop Machine Learning methodologies and protocols needed
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called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform advanced code optimizations that are hard to apply otherwise. Because of this, Tiramisu can generate fast code that outperforms highly
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) Demonstrated technical thought leadership in an applied computational field (e.g., computer vision, deep learning, numerical optimization, image analysis, computer game design, scientific computing, fine element
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The postdoc's primary mission will be to optimize feedback (critical incident technique) in high-security contexts using interview protocols developed within the framework of the scientific psychology
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. Computational Optimization: Resolving hardware-specific performance and numerical precision challenges across diverse GPU environments. Architecture Design: Leading the design of new loss functions, model