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reconstruction using Fourier domain optical normalization." Light-Science and Applications 5: el 60389, 2016. http://dx.doi.org/10.1038/Isa.2016.38 Henn MA, et al: "Optimizing the nanoscale quantitative optical
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of fellows: country/ies of residence: OTHER Eligibility of fellows: nationality/ies: OTHER Selection process To apply fill out the form available at the following website: https://careers.polito.it/ Website
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Posting Details Position Information Job Title Assistant/Associate/Full Professor Optimization and Statistics Posting Number P2233F Position Summary Information Job Description Summary The Auburn
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and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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integration of a non-intrusive power consumption monitoring (NILM) technology into an existing industrial optimization system. More specifically, the missions consist of: Participate in algorithmic and
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extensive electromagnetic modeling to optimize the waveguide structures for minimal loss, efficient confinement, and effective mode matching with external optical components. Particular attention will be
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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DFT, beyond-DFT, and experimental techniques. We are also interested in developing both forward and inverse machine learning models to accelerate and optimize the design processes. We work in close
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, operation, and optimization of SPS- and PLC-based control systems for experimental equipment and beamline instrumention Integration of hardware and software interfaces (motors, detectors, sensors, sample
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, layout generation, nanofabrication, laboratory characterization and application development. Experiment automation, measurement optimization, hardware and software development for collection and processing