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-transparent materials, and the utilisation of deep learning algorithms to accelerate computational solutions. Scientific Objectives Develop a self-contained finite volume solver for solidification of multiphase
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work environment. We are seeking a part-time Research Assistant in computer vision and machine learning for human behavior analysis and modeling. The successful candidate will investigate new algorithms
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on the design and performance analysis of resource allocation algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project "Utility Optimization
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed
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mathematical theory and algorithm development as well as engineering methods that enable robust and efficient practical solutions. As society and technology evolve toward increasingly large‑scale, data‑intensive
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platform integrating advanced robotics, materials characterization systems, digital twins and AI-based decision-making algorithms for accelerated research. The platform will incorporate explainable AI
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offers and actions on https://cluster-ia-enact.ai/ . You will work in a rare environment at the intersection of frugal AI, analog computing, reconfigurable electronics and THz imaging. The PhD is directly
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stability (beam break-up). The Grenoble Laboratory of Subatomic Physics and Cosmology (LPSC) ( http://lpsc.in2p3.fr ) is a mixed research unit associating CNRS-IN2P3, Grenoble Alpes University (UGA) and