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EPSRC-funded project, MAPFSI that will be focused on developing experimentally-validated computational algorithms for fluid-structure interaction problems including multiphysics effect of electromagnetism
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algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient computational methods to optimize wind farm performance, which in turn
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fundamentally more energy-efficient Computational Fluid Dynamics algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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guiding the development of advanced impact-resistant materials. The main purpose of this role is to develop multi-physics computational models and reveal liquid-solid impact damage mechanisms. The post will
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) Assessing the performance and fault tolerance of neuromorphic hardware; (b) Designing and developing one or more machine learning (ML) and artificial intelligence (AI) algorithms to support and enhance
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qualified candidates to apply for a postdoctoral research position. The research will focus on statistical modeling, machine learning and trustworthy AI to develop effective and efficient algorithms
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realizations and proven theoretical advantages. The project may involve several aspects, including mathematical theory, algorithm development, error correction, adaptation of GBS-based algorithms to other
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following good software development practices. Planning algorithms for autonomous systems. The candidate will be part of the new NYU Center for Robotics and Embodied Intelligence at NYU Tandon School