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Field
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engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g
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to climate change) under the supervision of Dr. Ashley Shade in the “Bacterial Efflux and Environmental Resistance” team. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5557-BEABIG-045
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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signal processing methods and a modelling environment, aided by unique hardware-in-the loop, to assess the detection and estimation algorithm performance and determine optimal multistatic configurations
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-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications
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to investigate all aspects of biogenic dyes, from the identification of dye-producing bacteria and the characterization of their pigments, through the optimization of their production and application
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intelligence (e.g., reinforcement learning for scheduling, congestion control, link adaptation, and cross-layer optimization). The exact research direction will be refined based on the candidate’s background and
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machine learning to generate more accurate demand and supply predictions, which will then be used in the optimization process. The project will also investigate the strategic use of real-time sensor inputs
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
platform Implement and optimize system architectures, including optical setups, control systems, and measurement pipelines Characterize, benchmark, and iteratively improve system performance using advanced
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the selection procedure. If you have any questions about the online application form, please check https://www.uantwerpen.be/en/jobs/apply-online-uantwerp/ or send an email to jobs@uantwerpen.be . If you have