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project within the SusMax network focused on developing interpretable machine-learning frameworks for kinetic multiphase reaction-network discovery in the catalytic conversion of renewable feedstocks
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. In this role, the selected candidate will be responsible for designing, developing, and optimising algorithms for processing and analysing signals in real-time applications. Responsibilities include
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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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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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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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interaction physics, precision calculations of (g-2) and PDF determinations, and the development of new algorithms, among others. Position Description The successful candidate will be expected to conduct
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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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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