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related fields Expert knowledge of building air-conditioning and mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat
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for robotics, electrical and digital control systems, sensors and sensor networks within the Advanced Manufacturing specialisation through the UTAS Virtual Learning Environment (VLE) Foster student success and
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-Senftenberg (BTU) combines top-level research and knowledge transfer at an international level, thereby creating an interdisciplinary innovation network and an excellent hub for science and technology. Together
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passionate about applying ML algorithms and developing AI applied research and innovation solutions using classic ML to novel transformer neural networks. We test and measure the real customer impact of each
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the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes
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responsibilities. Experience Essential: E1 Experience of analysing human body movement from sensor data (eg RGB videos and/or MOCAP data) using Deep Neural Networks (such as Graph Convolutional Networks). E2
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annual leave, plus 9 buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards
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implementation of the sensor network in strategic tourist locations • Identification and analysis of installation locations based on historical congestion patterns. • LoRa coverage planning, including
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Supervisor: Tenured Associate Professor Serkan Turkmen, Estonian Maritime Academy: Estonian Maritime Academy: Green Maritime Technology Research Group Proposed Thesis: Towards net zero in Maritime Industry
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/m/d) Development of soft-sensors connected to particlebased separation models to control flotation processes. Your tasks Develop and implement soft‑sensor concepts for continuous monitoring of ore