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Field
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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sensing technologies (camera, Electromagnetic tracking system, FBG sensing) with continuum robotic systems and development of associated sensing and estimation algorithms 3D environment reconstruction based
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and genomic data from distinct studies. Maintaining accurate code repositories for quality control and analytical algorithms Manages storage drives and maintains datasets. Required Education and
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genuine intellectual exchange, direct technical engagement in algorithm and model development, and shared co-ownership of the science. • Active Collaboration. The PI maintains an open-door policy, meets
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Systems At the Institute of Climate and Energy Research – Energy Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimising decentralised, integrated energy
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(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members
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to architectures, algorithms, and applications. Titled "Exploring Atomic Ensemble Qubits for Distributed Quantum Computing," this LBNL-funded initiative brings together experts from the ESnet, NERSC, and AMCR
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
: speech processing, computer vision, machine learning, solid programmming skills interest in connecting AI with human cognition Prior experience with LLM, SpeechLMs, RL algorithms, or robotic platforms is a
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 21 days ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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algorithms at scale on ORNL's computational resources, including the Frontier supercomputer, addressing critical challenges in science and engineering. Communicate and coordinate experimental results with