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frequencies of different UAV categories for different power settings shall be modelled. Second, based on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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advanced simulation methods, including Reynolds-Averaged Navier-Stokes (RANS), Direct Numerical Simulations (DNS), and/or Large Eddy Simulations (LES), will be employed to accurately model the complex flow
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conferences Requirements: a university degree in the field of computer science, data science, computational modeling or related subjects in combination with civil engineering, transport engineering a strong
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Kerryn Butler-Henderson via kerryn.butler-henderson@rmit.edu.au by 31 October 2022, with: A cover letter - outlining interest and alignment with the proposed research (see Further Information) A copy of
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to enhance the UK’s energy system resilience through a whole-system analysis approach. Building on the proven WeSIM model, RENEW will upgrade its capabilities to incorporate electrified district heating and
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characterization and benchmarking protocols for their suitability to provide efficient cost functions for the optimal control of gate calibration in full-stack quantum computers and simulators. Based on your
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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electron microscopy image simulations Development of a machine learning model capable of inferring 3D atomic structure from two-dimensional TEM projection images Application of the new approach
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develop data-inspired and data-driven models of sarcomere assembly. This will involve mean-field models and agent-based simulations. Additionally, depending on your aptitude, you can analyze topological