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on the following objectives: - Conduct a state-of-the-art review of existing databases and analyze their biases (e.g., precision of detection boxes). - Propose a semi-automatic pipeline for correcting these biases
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doors, accommodation space fire sprinkler system, fire detection system, machinery space water fog system, machinery space INERGEN fire suppression system, local fire suppression systems. AUTOMATION and
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for any employer without sponsorship. Purpose Administers and maintains systems, servers, networks, and virtual machines in support of clients. Responsibilities Responsible for installing, configuring
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University of North Carolina at Greensboro | Greensboro, Indiana | United States | about 7 hours ago
affordable institution in North Carolina for net cost by the N.Y. Times and No. 1 in North Carolina for social mobility by The Wall Street Journal — helping first-generation and lower-income students find
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NETWORK TECHNICIAN II-ENT - (T238453) Description FOR USE BY IT AND HSIS ONLY: To manage moderately complex tasks typically relating to network monitoring, operations, installation and/or
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) / PhD Position (m/f/x) (100 %, salary plus allowances package according to the Marie Skłodowska-Curie Actions (MSCA) – Doctoral Networks rules) for a period of 3 years. Selection is based on suitability
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find more detail on all of this and more at https://www.qub.ac.uk/directorates/HumanResources/pay-reward-and-benefits/ . Queen's University is committed to promoting equality of opportunity to all. We
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to anticipate, detect and respond to emerging viral threats at an earlier stage than before. Coordinated by Prof. Dr. Heli Harvala, Professor of Virology at the University of Turku in Finland, the network brings
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: Comprehensive technical knowledge of IT systems, hardware, software, and networking principles. Proven experience leading and managing a team within a customer-facing IT support environment, with responsibility
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100%, Zurich, fixed-term The Algorithms and Visualization Group in the Social Networks Lab at ETH Zürich is headed by Prof. Dr. Ulrik Brandes. We develop network data science methods