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(specifically PCECs). Proven experience in developing and validating numerical models (e.g., using COMSOL). Hands-on experience with programming for numerical optimization, machine learning, and data processing
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coordinates with the clinical staff, supply chain, and billing departments to identify discrepancies, resolve charge-related issues, improve documentation compliance, and optimize revenue integrity and
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but not limited to: o Quantum error correction, fault tolerance, and resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and
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, highlighting that current (pre)rehabilitation strategies do not effectively promote physical activity. Nevertheless, sufficient physical activity is essential to optimize surgical recovery and achieve broader
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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and economy that respect people and their environment. We are looking for our future postdoctoral researcher in optimization for statistical learning to join the Image, Data, Signal (IDS) department
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numerical methods for the inverse design of nanophotonic structures enabling broadband, multiparameter sensing in fiber-based systems. The project is a collaboration between AMOLF, TU Eindhoven, and
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will play a key role in strengthening and expanding the group’s computational capabilities for the simulation, analysis, and optimization of advanced thermal energy systems and processes. This includes
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project on the development of smart optical sensors for environmental monitoring in the oil & gas industry. Our photonics research lab has set modern tools for the design, testing, and optimization
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provide detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking