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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
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project on convergence analysis of reinforcement learning algorithms for partially observed environments. The position is at the intersection of machine learning, stochastic analysis, and dynamical systems
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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developing image analysis and machine learning algorithms and tools for aerial imaging and analysis. You will also contribute to data collection, data curation, and the development of a data portal for project
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work independently on complex projects. Experience and Education Master’s degree in Software and Computer Engineering (French engineering schools are preferred). Experience in optimizing ML algorithms
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AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum
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a training dataset for developing machine learning algorithms for increasing the consistency of quality control in two cohort studies: healthy controls and epilepsy patients. Key Responsibilities
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and synthesize relevant literature in machine learning, representation learning, and manifold learning. Propose and implement extensions to existing dimension reduction algorithms using contrastive