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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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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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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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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
. Experience in machine learning algorithms and tools. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary teams. Strong analytical reasoning and persistence in experimental
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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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terrain, the co-evolution of morphology and control for soft and legged robots using differentiable and evolutionary optimisation, and gravity-aware locomotion strategies for mass- and energy-limited
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and complex system simulations develop, implement, test, and benchmark computational models, algorithms, data pipelines, and research software prototypes contribute to optimisation, simulation, sampling
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, algorithms, data pipelines, and research software prototypes contribute to optimisation, simulation, sampling, or uncertainty-modelling approaches for complex systems analyse infrastructure, spatial, temporal
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, algorithms, data pipelines, and research software prototypes contribute to optimisation, simulation, sampling, or uncertainty-modelling approaches for complex systems analyse infrastructure, spatial, temporal
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, artificial intelligence, network science, Bayesian methods, spatiotemporal methods, visualization, evolutionary game theory, infectious disease modeling, and assistive and accessibility technologies, with a