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Field
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nonlinear, ultrafast, and integrated photonics. Develop predictive theoretical and computational models for optical materials and photonic devices. Perform numerical modelling and simulation of optical
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, stochastic thermodynamics, and quantum physics. The research will focus on three main directions: Thermodynamic computing: developing physics-inspired alternative models of computation that aim to reduce
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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Requisition Id 16167 Overview: The Multiphysics Modeling and Flows (MMF) Group in the Computational Sciences and Engineering Division is seeking a Postdoctoral Research Associate with expertise in
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 23 days ago
) at the IT4Innovations, in the Material Design group of Dr. Dominik Legut within the Modeling of Nanotechnology Lab, is open to applicants for the SPIN DYNAMICAL CALCULATIONS of the topics of Czech Science Foundation’s
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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Institut Polytechnique de Paris, is one of France's top 5 general engineering schools. The mainspring of Télécom Paris is to train, imagine and undertake to design digital models, technologies and solutions
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of conceptual and numerical models describing sediment material properties, sediment and water transport, leveraging in-situ and indirect measurements such as geophysical and/or remote sensing
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in development and validation of multiscale numerical modeling techniques. Additional Application Materials Required: Special Instructions to the Applicants: Applications should include: (i) a cover
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of reproducing aerodynamic loads in real time for physical experiments. The project combines numerical modelling, data-driven methods, and laboratory experimentation to advance next-generation real-time hybrid